(upbeat music) >> Hello and welcome to theCube's coverage of International Women's Day. I'm John Furrier, your host of "theCUBE." We've got great two remote guests coming into our Palo Alto Studios, some tech athletes, as we say, people that've been in the trenches, years of experience, Lena Smart, CISO at MongoDB, Cube alumni, and Tara Hernandez, VP of Developer Productivity at MongoDB as well. Thanks for coming in to this program and supporting our efforts today. Thanks so much. >> Thanks for having us. >> Yeah, everyone talk about the journey in tech, where it all started. Before we get there, talk about what you guys are doing at MongoDB specifically. MongoDB is kind of gone the next level as a platform. You have your own ecosystem, lot of developers, very technical crowd, but it's changing the business transformation. What do you guys do at Mongo? We'll start with you, Lena. >> So I'm the CISO, so all security goes through me. I like to say, well, I don't like to say, I'm described as the ones throat to choke. So anything to do with security basically starts and ends with me. We do have a fantastic Cloud engineering security team and a product security team, and they don't report directly to me, but obviously we have very close relationships. I like to keep that kind of church and state separate and I know I've spoken about that before. And we just recently set up a physical security team with an amazing gentleman who left the FBI and he came to join us after 26 years for the agency. So, really starting to look at the physical aspects of what we offer as well. >> I interviewed a CISO the other day and she said, "Every day is day zero for me." Kind of goofing on the Amazon Day one thing, but Tara, go ahead. Tara, go ahead. What's your role there, developer productivity? What are you focusing on? >> Sure. Developer productivity is kind of the latest description for things that we've described over the years as, you know, DevOps oriented engineering or platform engineering or build and release engineering development infrastructure. It's all part and parcel, which is how do we actually get our code from developer to customer, you know, and all the mechanics that go into that. It's been something I discovered from my first job way back in the early '90s at Borland. And the art has just evolved enormously ever since, so. >> Yeah, this is a very great conversation both of you guys, right in the middle of all the action and data infrastructures changing, exploding, and involving big time AI and data tsunami and security never stops. Well, let's get into, we'll talk about that later, but let's get into what motivated you guys to pursue a career in tech and what were some of the challenges that you faced along the way? >> I'll go first. The fact of the matter was I intended to be a double major in history and literature when I went off to university, but I was informed that I had to do a math or a science degree or else the university would not be paid for. At the time, UC Santa Cruz had a policy that called Open Access Computing. This is, you know, the late '80s, early '90s. And anybody at the university could get an email account and that was unusual at the time if you were, those of us who remember, you used to have to pay for that CompuServe or AOL or, there's another one, I forget what it was called, but if a student at Santa Cruz could have an email account. And because of that email account, I met people who were computer science majors and I'm like, "Okay, I'll try that." That seems good. And it was a little bit of a struggle for me, a lot I won't lie, but I can't complain with how it ended up. And certainly once I found my niche, which was development infrastructure, I found my true love and I've been doing it for almost 30 years now. >> Awesome. Great story. Can't wait to ask a few questions on that. We'll go back to that late '80s, early '90s. Lena, your journey, how you got into it. >> So slightly different start. I did not go to university. I had to leave school when I was 16, got a job, had to help support my family. Worked a bunch of various jobs till I was about 21 and then computers became more, I think, I wouldn't say they were ubiquitous, but they were certainly out there. And I'd also been saving up every penny I could earn to buy my own computer and bought an Amstrad 1640, 20 meg hard drive. It rocked. And kind of took that apart, put it back together again, and thought that could be money in this. And so basically just teaching myself about computers any job that I got. 'Cause most of my jobs were like clerical work and secretary at that point. But any job that had a computer in front of that, I would make it my business to go find the guy who did computing 'cause it was always a guy. And I would say, you know, I want to learn how these work. Let, you know, show me. And, you know, I would take my lunch hour and after work and anytime I could with these people and they were very kind with their time and I just kept learning, so yep. >> Yeah, those early days remind me of the inflection point we're going through now. This major C change coming. Back then, if you had a computer, you had to kind of be your own internal engineer to fix things. Remember back on the systems revolution, late '80s, Tara, when, you know, your career started, those were major inflection points. Now we're seeing a similar wave right now, security, infrastructure. It feels like it's going to a whole nother level. At Mongo, you guys certainly see this as well, with this AI surge coming in. A lot more action is coming in. And so there's a lot of parallels between these inflection points. How do you guys see this next wave of change? Obviously, the AI stuff's blowing everyone away. Oh, new user interface. It's been called the browser moment, the mobile iPhone moment, kind of for this generation. There's a lot of people out there who are watching that are young in their careers, what's your take on this? How would you talk to those folks around how important this wave is? >> It, you know, it's funny, I've been having this conversation quite a bit recently in part because, you know, to me AI in a lot of ways is very similar to, you know, back in the '90s when we were talking about bringing in the worldwide web to the forefront of the world, right. And we tended to think in terms of all the optimistic benefits that would come of it. You know, free passing of information, availability to anyone, anywhere. You just needed an internet connection, which back then of course meant a modem. >> John: Not everyone had though. >> Exactly. But what we found in the subsequent years is that human beings are what they are and we bring ourselves to whatever platforms that are there, right. And so, you know, as much as it was amazing to have this freely available HTML based internet experience, it also meant that the negatives came to the forefront quite quickly. And there were ramifications of that. And so to me, when I look at AI, we're already seeing the ramifications to that. Yes, are there these amazing, optimistic, wonderful things that can be done? Yes. >> Yeah. >> But we're also human and the bad stuff's going to come out too. And how do we- >> Yeah. >> How do we as an industry, as a community, you know, understand and mitigate those ramifications so that we can benefit more from the positive than the negative. So it is interesting that it comes kind of full circle in really interesting ways. >> Yeah. The underbelly takes place first, gets it in the early adopter mode. Normally industries with, you know, money involved arbitrage, no standards. But we've seen this movie before. Is there hope, Lena, that we can have a more secure environment? >> I would hope so. (Lena laughs) Although depressingly, we've been in this well for 30 years now and we're, at the end of the day, still telling people not to click links on emails. So yeah, that kind of still keeps me awake at night a wee bit. The whole thing about AI, I mean, it's, obviously I am not an expert by any stretch of the imagination in AI. I did read (indistinct) book recently about AI and that was kind of interesting. And I'm just trying to teach myself as much as I can about it to the extent of even buying the "Dummies Guide to AI." Just because, it's actually not a dummies guide. It's actually fairly interesting, but I'm always thinking about it from a security standpoint. So it's kind of my worst nightmare and the best thing that could ever happen in the same dream. You know, you've got this technology where I can ask it a question and you know, it spits out generally a reasonable answer. And my team are working on with Mark Porter our CTO and his team on almost like an incubation of AI link. What would it look like from MongoDB? What's the legal ramifications? 'Cause there will be legal ramifications even though it's the wild, wild west just now, I think. Regulation's going to catch up to us pretty quickly, I would think. >> John: Yeah, yeah. >> And so I think, you know, as long as companies have a seat at the table and governments perhaps don't become too dictatorial over this, then hopefully we'll be in a good place. But we'll see. I think it's a really interest, there's that curse, we're living in interesting times. I think that's where we are. >> It's interesting just to stay on this tech trend for a minute. The standards bodies are different now. Back in the old days there were, you know, IEEE standards, ITF standards. >> Tara: TPC. >> The developers are the new standard. I mean, now you're seeing open source completely different where it was in the '90s to here beginning, that was gen one, some say gen two, but I say gen one, now we're exploding with open source. You have kind of developers setting the standards. If developers like it in droves, it becomes defacto, which then kind of rolls into implementation. >> Yeah, I mean I think if you don't have developer input, and this is why I love working with Tara and her team so much is 'cause they get it. If we don't have input from developers, it's not going to get used. There's going to be ways of of working around it, especially when it comes to security. If they don't, you know, if you're a developer and you're sat at your screen and you don't want to do that particular thing, you're going to find a way around it. You're a smart person. >> Yeah. >> So. >> Developers on the front lines now versus, even back in the '90s, they're like, "Okay, consider the dev's, got a QA team." Everything was Waterfall, now it's Cloud, and developers are on the front lines of everything. Tara, I mean, this is where the standards are being met. What's your reaction to that? >> Well, I think it's outstanding. I mean, you know, like I was at Netscape and part of the crowd that released the browser as open source and we founded mozilla.org, right. And that was, you know, in many ways kind of the birth of the modern open source movement beyond what we used to have, what was basically free software foundation was sort of the only game in town. And I think it is so incredibly valuable. I want to emphasize, you know, and pile onto what Lena was saying, it's not just that the developers are having input on a sort of company by company basis. Open source to me is like a checks and balance, where it allows us as a broader community to be able to agree on and enforce certain standards in order to try and keep the technology platforms as accessible as possible. I think Kubernetes is a great example of that, right. If we didn't have Kubernetes, that would've really changed the nature of how we think about container orchestration. But even before that, Linux, right. Linux allowed us as an industry to end the Unix Wars and as someone who was on the front lines of that as well and having to support 42 different operating systems with our product, you know, that was a huge win. And it allowed us to stop arguing about operating systems and start arguing about software or not arguing, but developing it in positive ways. So with, you know, with Kubernetes, with container orchestration, we all agree, okay, that's just how we're going to orchestrate. Now we can build up this huge ecosystem, everybody gets taken along, right. And now it changes the game for what we're defining as business differentials, right. And so when we talk about crypto, that's a little bit harder, but certainly with AI, right, you know, what are the checks and balances that as an industry and as the developers around this, that we can in, you know, enforce to make sure that no one company or no one body is able to overly control how these things are managed, how it's defined. And I think that is only for the benefit in the industry as a whole, particularly when we think about the only other option is it gets regulated in ways that do not involve the people who actually know the details of what they're talking about. >> Regulated and or thrown away or bankrupt or- >> Driven underground. >> Yeah. >> Which would be even worse actually. >> Yeah, that's a really interesting, the checks and balances. I love that call out. And I was just talking with another interview part of the series around women being represented in the 51% ratio. Software is for everybody. So that we believe that open source movement around the collective intelligence of the participants in the industry and independent of gender, this is going to be the next wave. You're starting to see these videos really have impact because there are a lot more leaders now at the table in companies developing software systems and with AI, the aperture increases for applications. And this is the new dynamic. What's your guys view on this dynamic? How does this go forward in a positive way? Is there a certain trajectory you see? For women in the industry? >> I mean, I think some of the states are trying to, again, from the government angle, some of the states are trying to force women into the boardroom, for example, California, which can be no bad thing, but I don't know, sometimes I feel a bit iffy about all this kind of forced- >> John: Yeah. >> You know, making, I don't even know how to say it properly so you can cut this part of the interview. (John laughs) >> Tara: Well, and I think that they're >> I'll say it's not organic. >> No, and I think they're already pulling it out, right. It's already been challenged so they're in the process- >> Well, this is the open source angle, Tara, you are getting at it. The change agent is open, right? So to me, the history of the proven model is openness drives transparency drives progress. >> No, it's- >> If you believe that to be true, this could have another impact. >> Yeah, it's so interesting, right. Because if you look at McKinsey Consulting or Boston Consulting or some of the other, I'm blocking on all of the names. There has been a decade or more of research that shows that a non homogeneous employee base, be it gender or ethnicity or whatever, generates more revenue, right? There's dollar signs that can be attached to this, but it's not enough for all companies to want to invest in that way. And it's not enough for all, you know, venture firms or investment firms to grant that seed money or do those seed rounds. I think it's getting better very slowly, but socialization is a much harder thing to overcome over time. Particularly, when you're not just talking about one country like the United States in our case, but around the world. You know, tech centers now exist all over the world, including places that even 10 years ago we might not have expected like Nairobi, right. Which I think is amazing, but you have to factor in the cultural implications of that as well, right. So yes, the openness is important and we have, it's important that we have those voices, but I don't think it's a panacea solution, right. It's just one more piece. I think honestly that one of the most important opportunities has been with Cloud computing and Cloud's been around for a while. So why would I say that? It's because if you think about like everybody holds up the Steve Jobs, Steve Wozniak, back in the '70s, or Sergey and Larry for Google, you know, you had to have access to enough credit card limit to go to Fry's and buy your servers and then access to somebody like Susan Wojcicki to borrow the garage or whatever. But there was still a certain amount of upfrontness that you had to be able to commit to, whereas now, and we've, I think, seen a really good evidence of this being able to lease server resources by the second and have development platforms that you can do on your phone. I mean, for a while I think Africa, that the majority of development happened on mobile devices because there wasn't a sufficient supply chain of laptops yet. And that's no longer true now as far as I know. But like the power that that enables for people who would otherwise be underrepresented in our industry instantly opens it up, right? And so to me that's I think probably the biggest opportunity that we've seen from an industry on how to make more availability in underrepresented representation for entrepreneurship. >> Yeah. >> Something like AI, I think that's actually going to take us backwards if we're not careful. >> Yeah. >> Because of we're reinforcing that socialization. >> Well, also the bias. A lot of people commenting on the biases of the large language inherently built in are also problem. Lena, I want you to weigh on this too, because I think the skills question comes up here and I've been advocating that you don't need the pedigree, college pedigree, to get into a certain jobs, you mentioned Cloud computing. I mean, it's been around for you think a long time, but not really, really think about it. The ability to level up, okay, if you're going to join something new and half the jobs in cybersecurity are created in the past year, right? So, you have this what used to be a barrier, your degree, your pedigree, your certification would take years, would be a blocker. Now that's gone. >> Lena: Yeah, it's the opposite. >> That's, in fact, psychology. >> I think so, but the people who I, by and large, who I interview for jobs, they have, I think security people and also I work with our compliance folks and I can't forget them, but let's talk about security just now. I've always found a particular kind of mindset with security folks. We're very curious, not very good at following rules a lot of the time, and we'd love to teach others. I mean, that's one of the big things stem from the start of my career. People were always interested in teaching and I was interested in learning. So it was perfect. And I think also having, you know, strong women leaders at MongoDB allows other underrepresented groups to actually apply to the company 'cause they see that we're kind of talking the talk. And that's been important. I think it's really important. You know, you've got Tara and I on here today. There's obviously other senior women at MongoDB that you can talk to as well. There's a bunch of us. There's not a whole ton of us, but there's a bunch of us. And it's good. It's definitely growing. I've been there for four years now and I've seen a growth in women in senior leadership positions. And I think having that kind of track record of getting really good quality underrepresented candidates to not just interview, but come and join us, it's seen. And it's seen in the industry and people take notice and they're like, "Oh, okay, well if that person's working, you know, if Tara Hernandez is working there, I'm going to apply for that." And that in itself I think can really, you know, reap the rewards. But it's getting started. It's like how do you get your first strong female into that position or your first strong underrepresented person into that position? It's hard. I get it. If it was easy, we would've sold already. >> It's like anything. I want to see people like me, my friends in there. Am I going to be alone? Am I going to be of a group? It's a group psychology. Why wouldn't? So getting it out there is key. Is there skills that you think that people should pay attention to? One's come up as curiosity, learning. What are some of the best practices for folks trying to get into the tech field or that's in the tech field and advancing through? What advice are you guys- >> I mean, yeah, definitely, what I say to my team is within my budget, we try and give every at least one training course a year. And there's so much free stuff out there as well. But, you know, keep learning. And even if it's not right in your wheelhouse, don't pick about it. Don't, you know, take a look at what else could be out there that could interest you and then go for it. You know, what does it take you few minutes each night to read a book on something that might change your entire career? You know, be enthusiastic about the opportunities out there. And there's so many opportunities in security. Just so many. >> Tara, what's your advice for folks out there? Tons of stuff to taste, taste test, try things. >> Absolutely. I mean, I always say, you know, my primary qualifications for people, I'm looking for them to be smart and motivated, right. Because the industry changes so quickly. What we're doing now versus what we did even last year versus five years ago, you know, is completely different though themes are certainly the same. You know, we still have to code and we still have to compile that code or package the code and ship the code so, you know, how well can we adapt to these new things instead of creating floppy disks, which was my first job. Five and a quarters, even. The big ones. >> That's old school, OG. There it is. Well done. >> And now it's, you know, containers, you know, (indistinct) image containers. And so, you know, I've gotten a lot of really great success hiring boot campers, you know, career transitioners. Because they bring a lot experience in addition to the technical skills. I think the most important thing is to experiment and figuring out what do you like, because, you know, maybe you are really into security or maybe you're really into like deep level coding and you want to go back, you know, try to go to school to get a degree where you would actually want that level of learning. Or maybe you're a front end engineer, you want to be full stacked. Like there's so many different things, data science, right. Maybe you want to go learn R right. You know, I think it's like figure out what you like because once you find that, that in turn is going to energize you 'cause you're going to feel motivated. I think the worst thing you could do is try to force yourself to learn something that you really could not care less about. That's just the worst. You're going in handicapped. >> Yeah and there's choices now versus when we were breaking into the business. It was like, okay, you software engineer. They call it software engineering, that's all it was. You were that or you were in sales. Like, you know, some sort of systems engineer or sales and now it's,- >> I had never heard of my job when I was in school, right. I didn't even know it was a possibility. But there's so many different types of technical roles, you know, absolutely. >> It's so exciting. I wish I was young again. >> One of the- >> Me too. (Lena laughs) >> I don't. I like the age I am. So one of the things that I did to kind of harness that curiosity is we've set up a security champions programs. About 120, I guess, volunteers globally. And these are people from all different backgrounds and all genders, diversity groups, underrepresented groups, we feel are now represented within this champions program. And people basically give up about an hour or two of their time each week, with their supervisors permission, and we basically teach them different things about security. And we've now had seven full-time people move from different areas within MongoDB into my team as a result of that program. So, you know, monetarily and time, yeah, saved us both. But also we're showing people that there is a path, you know, if you start off in Tara's team, for example, doing X, you join the champions program, you're like, "You know, I'd really like to get into red teaming. That would be so cool." If it fits, then we make that happen. And that has been really important for me, especially to give, you know, the women in the underrepresented groups within MongoDB just that window into something they might never have seen otherwise. >> That's a great common fit is fit matters. Also that getting access to what you fit is also access to either mentoring or sponsorship or some sort of, at least some navigation. Like what's out there and not being afraid to like, you know, just ask. >> Yeah, we just actually kicked off our big mentor program last week, so I'm the executive sponsor of that. I know Tara is part of it, which is fantastic. >> We'll put a plug in for it. Go ahead. >> Yeah, no, it's amazing. There's, gosh, I don't even know the numbers anymore, but there's a lot of people involved in this and so much so that we've had to set up mentoring groups rather than one-on-one. And I think it was 45% of the mentors are actually male, which is quite incredible for a program called Mentor Her. And then what we want to do in the future is actually create a program called Mentor Them so that it's not, you know, not just on the female and so that we can live other groups represented and, you know, kind of break down those groups a wee bit more and have some more granularity in the offering. >> Tara, talk about mentoring and sponsorship. Open source has been there for a long time. People help each other. It's community-oriented. What's your view of how to work with mentors and sponsors if someone's moving through ranks? >> You know, one of the things that was really interesting, unfortunately, in some of the earliest open source communities is there was a lot of pervasive misogyny to be perfectly honest. >> Yeah. >> And one of the important adaptations that we made as an open source community was the idea, an introduction of code of conducts. And so when I'm talking to women who are thinking about expanding their skills, I encourage them to join open source communities to have opportunity, even if they're not getting paid for it, you know, to develop their skills to work with people to get those code reviews, right. I'm like, "Whatever you join, make sure they have a code of conduct and a good leadership team. It's very important." And there are plenty, right. And then that idea has come into, you know, conferences now. So now conferences have codes of contact, if there are any good, and maybe not all of them, but most of them, right. And the ideas of expanding that idea of intentional healthy culture. >> John: Yeah. >> As a business goal and business differentiator. I mean, I won't lie, when I was recruited to come to MongoDB, the culture that I was able to discern through talking to people, in addition to seeing that there was actually women in senior leadership roles like Lena, like Kayla Nelson, that was a huge win. And so it just builds on momentum. And so now, you know, those of us who are in that are now representing. And so that kind of reinforces, but it's all ties together, right. As the open source world goes, particularly for a company like MongoDB, which has an open source product, you know, and our community builds. You know, it's a good thing to be mindful of for us, how we interact with the community and you know, because that could also become an opportunity for recruiting. >> John: Yeah. >> Right. So we, in addition to people who might become advocates on Mongo's behalf in their own company as a solution for themselves, so. >> You guys had great successful company and great leadership there. I mean, I can't tell you how many times someone's told me "MongoDB doesn't scale. It's going to be dead next year." I mean, I was going back 10 years. It's like, just keeps getting better and better. You guys do a great job. So it's so fun to see the success of developers. Really appreciate you guys coming on the program. Final question, what are you guys excited about to end the segment? We'll give you guys the last word. Lena will start with you and Tara, you can wrap us up. What are you excited about? >> I'm excited to see what this year brings. I think with ChatGPT and its copycats, I think it'll be a very interesting year when it comes to AI and always in the lookout for the authentic deep fakes that we see coming out. So just trying to make people aware that this is a real thing. It's not just pretend. And then of course, our old friend ransomware, let's see where that's going to go. >> John: Yeah. >> And let's see where we get to and just genuine hygiene and housekeeping when it comes to security. >> Excellent. Tara. >> Ah, well for us, you know, we're always constantly trying to up our game from a security perspective in the software development life cycle. But also, you know, what can we do? You know, one interesting application of AI that maybe Google doesn't like to talk about is it is really cool as an addendum to search and you know, how we might incorporate that as far as our learning environment and developer productivity, and how can we enable our developers to be more efficient, productive in their day-to-day work. So, I don't know, there's all kinds of opportunities that we're looking at for how we might improve that process here at MongoDB and then maybe be able to share it with the world. One of the things I love about working at MongoDB is we get to use our own products, right. And so being able to have this interesting document database in order to put information and then maybe apply some sort of AI to get it out again, is something that we may well be looking at, if not this year, then certainly in the coming year. >> Awesome. Lena Smart, the chief information security officer. Tara Hernandez, vice president developer of productivity from MongoDB. Thank you so much for sharing here on International Women's Day. We're going to do this quarterly every year. We're going to do it and then we're going to do quarterly updates. Thank you so much for being part of this program. >> Thank you. >> Thanks for having us. >> Okay, this is theCube's coverage of International Women's Day. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(upbeat intro music) >> Good afternoon, fellow tech nerds. My name is Savannah Peterson, coming to you from theCube's Remote Studio here in Motown, Detroit, Michigan where we are at KubeCon. John, this is our 12th interview of the day. How are you feeling? >> I'm feeling fresh as the first interview. (Savannah laughs) As always. >> That delivery really implied a level of freshness. >> Let's go! No, this is only Day 1. In three days, reinvent. We go hardcore. These are great events. We get so much great content. The conversations are amazing. The guests are awesome. They're technical, they're smart, and they're making the difference in the future. So, this next segment about Scale MySQL should be awesome. >> I am very excited to introduce our next guest who actually has a Twitter handle that I think most people, at least of my gender in this industry would love to have. She is @ATechGirl. So you can go ahead and tweet her and tell her how great this interview is while we're live. Please welcome Deepthi Sigireddi. Thank you so much for being here with us. >> Thank you for having me. >> You're feeding us in. You've got two talks you're giving while we're here. >> Yes, yes. So tomorrow we will be talking about VTR, myself and one of the other maintainers of Vitess and on Friday we have the Vitess Maintainer Talk. All graduated projects get a maintainer talk. >> Wow, so you are like KubeCon VIP celebrity. >> Well, I hope so. >> Well, you're a maintainer and technical lead, also software engineer at the PlanetScale. But talk about the graduation process where that means to the project and the people involved. >> So Vitess graduated in 2019 and there are strict criteria for graduation and you don't just have to meet the minimum, you sort of have to over perform on the graduation criteria. Some of which are like there must be at least two large production deploys and people from those companies have to go in front of the CNCF committee that approves these things and say that, "Yes, this project is critical to our business." >> A lot of peer review, a lot of deployment success. >> Yes. >> Good consistency in the code. >> Deepthi: Community diversity. >> All that. >> All those things. >> Talk about the importance of this project. What is the top story that people should know about around the project? Why it exists, why it's important, why it's relevant, why it's cool. How would you answer that? >> So MySQL is now 30 years old and yet they are still- >> Makes me feel a little sidebar. (Deepthi laughs) Yeah. >> And yet even though there are many other newer databases, it continues to be used at many of the largest internet scale companies. And some of them, for example, Slack, GitHub, Square, they have grown to a level where they could not have if they had tried to do it with Vanilla MySQL that they started with, and the only reason they are where they are is Vitess. So that is I think the number one thing people should know about Vitess. >> And the origination story on notes say "Came from YouTube." >> Yes. So the way Vitess started was that YouTube was having problems with their MySQL deployment and they got tired of dealing with the site being down. So the founders of Vitess decided that they had to do something about it and they started building Vitess which started as a pretty small, relatively code-based with limited features, and over time they built charting and all of the other things that we have today. >> Well, this is exciting Savannah because we've seen this industry. Like with Facebook, when they started, everyone built their own stuff. MySQL was a great- >> Oh gosh, and everyone wanted to build it their way, reinventing the wheel. >> And MySQL was great. And then as it kind of broke when it grew, it got retrofitted. So, it was constantly being scaled up to the point where now you guys, if I get this right, said, "Hey, we're going to work on this. We're going to make it next-gen." So it's kind of like next-gen MySQL. Almost. >> Yes, yes. I would say that's pretty accurate, yeah. So there are still large companies which run their own MySQL and they have scaled it in their own way, but Vitess happens to be an open source way of scaling MySQL that people can adopt without having to build all of their own tooling around it. >> Speaking of that and growing, you just announced a new version today. >> Yes, yes. >> Tell us about that. >> The focus in this version was to make Vitess easier to use and to deploy. So in the past, there was one glaring gap in Vitess which was that Vitess did not automatically detect and repair MySQL level failures. With this release, we've actually closed that gap. And what that means for people using Vitess is that they will actually spend less time dealing with outages manually, or less human intervention, More automated recovery is what it means. The other thing we've released today is a new web UI. Vitess had a very old web UI, ugly, hard to maintain. Nobody liked it. But it was functional, except we couldn't add anything new to it because it was so old. So, the backend functionality kept advancing but the front end was kind of frozen. Now we have a next generation UI to which in upcoming releases we can add more and more functionality. >> So, it's extensible. They add things in. >> Deepthi: Oh yes, of course. Yeah. >> Awesome. What's the biggest thing that you like about the new situation? Is it more contributors are on board the UI? What's the fresh new impact that's happening in the community? What's getting you excited about with the current project? And the UI's great 'cause usability is important. >> Deepthi: Right. >> Scalability is important. >> I think Vitess solved the scalability problem way early and only now we are really grappling with the usability problem. So the hope and the desire is to make Vitess autopilot so that you reduce human intervention to a minimum once you deploy it. Obviously, you have to go through the process of deploying it. But once you've deployed it, it should just run itself. >> Runs at scale. So, the scale's huge? >> Deepthi: Yes. >> How many contributors are involved in the project? Can you give some numbers? Do you have any handy that you can speak to? >> Right. So, CNCF actually tracks these statistics for all the projects and we consolidated some numbers for the last two full calendar years, 2020 and 2021. We had over 400 contributors and 200 plus of them contributed code and the others contributed documentation issues, website changes, and things like that. So that gives- >> How about downloads? Download's good? >> Oh, okay. So we started publishing the current official Vitess Docker Image in 2018. And by October of 2020, we had about 3.8 million downloads. And by August of 2021, we had 5.2 million. And today, we have had over 10 million downloads- >> Wow! >> Of the main image. >> Starting to see a minute of that hockey stick that we all like to see. Seems like you're very clearly a community-first leader and it seems like that's in the PlanetScale and the test's DNA. Is that how the whole company culture views it? Would you say it's community-first business? >> PlanetScale is very much committed to Vitess as an open source project and to serving the Vitess community. So as part of my role at PlanetScale, some of the things I do are helping new contributors whether they are from PlanetScale or from outside PlanetScale. A number of PlanetScale engineers who don't work full-time on Vitess still contribute bug fixes and features to Vitess. We spend a significant amount of our energy helping users in our community Slack. The releases we do are mainly for the benefit of the community and PlanetScale is making those releases because for Planet Scale... Within PlanetScale, we actually do separate releases versus the public ones. >> One of the things that's coming up here at the show is deploying on Kubernetes. How does that look like? Everyone wants ease of use. Are you guys easy to use? >> Yes, yes. So PlanetScale also open sourced a Kubernetes operator for Vitess that people outside PlanetScale are using to run their production deployments of Vitess. Prior to that, there were Vitess users who actually built their own Kubernetes deployments of Vitess and they are still running those, but new users and new adopters of Vitess tend to use the Kubernetes operator that we are publishing. >> And you guys are the managed service for Vitess for the people that that's the business model for PlanetScale. >> Correct. So PlanetScale has a serverless database on demand which is built on Vitess. So if someone's starting something new and they just need a database, you sign up. It takes 30 seconds to get a database. Connect to it and start doing things with it. Versus if you are a large enterprise and you have a huge database deployment, you can migrate to PlanetScale, import all of your existing data, cut over with minimal downtime and then go, and then PlanetScale manages that. >> And why would they do that? What's the use case for that? Save time new development team or refactoring? >> Save time not being able to hire people with the skills to run it in-house. Not wanting to invest engineering resources in what businesses think is not their core competency. They want to focus on their business value. >> So, this database is a service in their whatever they're doing without adding more costs. >> Right. >> And speed. Okay, cool. How's that going? >> It's going well. >> Any feedback from customers in terms of why that there are any benefit statements you seek popping out? What are the big... What's the big aha when they... When people realize what they have here, what's the aha moment for them? Do they go, "Wow, this is awesome. It's so easy. Push a button. Migrate." Or is it... >> All of those. And people have actually seen cost savings when they've migrated from Amazon RDS to PlanetScale and we have testimonials from people who've said that, "It was so easy to use PlanetScale. Why would we try to do it ourselves?" >> It's the best thing a customer could say, right? We're all about being painkillers and solving some sort of problem. I think that that's a great opportunity to let you show off some of your customers. So, who is receiving this benefit? 'Cause I know PlanetScale specifically is for a certain style of business. >> Hmm. We have a list of customers on the website. >> Savannah: I was going to say you have a really- >> John: She's a software engineer. She's not marketing. >> You did sexy. >> You're doing a great job as much as marketing. >> So the reason I am bringing this up is because it's clear this is a solution for companies like Square, SoundCloud, Etsy, Jordan, and other exciting brands. So when you're talking about companies at scale, these companies are very much at scale, which is awesome. >> Yeah. >> What's next? What do you guys see the future for the project? >> I think we talked about that a little bit already. So, usability is a big thing. We did the new UI. It's not complete, right? Because over the last four years we've built more features into the backend which you can't yet access from the UI. So we want to be able for people to use things like online schema changes which is a big feature of Vitess. Doing schema changes without downtime from the UI. So, schema management from the UI. Vitess has something called VReplication which is the core technology that enables charting. And right now you can from the UI monitor your charting status, but you can't actually start charting from the UI. So more of the administrative functions we want to enable from the UI. >> John: Awesome. >> Last question. What are you personally most excited about this week being here with our wonderful community? >> I always enjoy being at KubeCon. This is my fifth or sixth in-person and I've done a couple of virtual ones. >> Savannah: Awesome. >> Because of the energy, because you get to meet people in person whom previously you've only met in Slack or maybe in a monthly community Zoom calls. We always have people come to our project booth. We have a project booth here for Vitess. People come to the company booth. PlanetScale has a booth. People come to our talks, ask questions. We end up having design discussions, architecture discussions. We get feedback on what is important to the people who show up here. That always informs what we do with the project in future releases. >> Perfect answer. I already mentioned that you can get a hold and in touch with Deepthi through her wonderful Twitter handle. Is there any other website or anything you want to shout out here before I do our close? >> vitess.io. V-I-T-E-S-S dot I-O is the Vitess website and planetscale.com is the PlanetScale website. >> Deepthi Sigireddi, thank you so much for being on the show with us today. John, thanks for keeping me company as always. >> You're welcome. >> And thank all of you for tuning into theCUBE. We will be here in Detroit, Michigan all week live from KubeCon and we hope to see you there. (gentle upbeat music)

(upbeat music) >> Hi everybody, this is Dave Vellante. And welcome to this CUBE conversation where we welcome an ESG senior analyst, Bob Laliberte Bob, good to see you. >> Great to see you too. Thanks for having me >> Love it, I love to have the analyst sessions. Set it up. What's your scope, what's your area of expertise? >> So my coverage area right now is networking in its entirety. So that spans everything from enterprise networking, wired, wireless, campus, data center, et cetera. All the way up through telco and, in cloud networking. >> So how do you look at the landscape? One of the big things I think about a lot is how does the shift to cloud migration? How does that affect the existing, network layers? I mean, you got Cisco as the big whale and it's just, it's amazing to me. They still have whatever percent market share they have 60, 65% of the market. Are things, what's happening in the competitive landscape. How is cloud affecting that? >> That's a great question. I think the interesting piece is so many times organizations think about the network as plumbing. But the reality is the it's really important plumbing because as you talk about cloud and things get more distributed, well, guess what connects those distributed locations? It's the network. And so organizations as they've moved to the cloud you've seen a big shift with things like SD-WAN and so forth. How do I get more efficient connectivity up to that cloud? How do I not only enable able better connectivity between my data centers in the cloud, but now all my remote workers in the cloud. And so there's been a lot of big shifts going on that have driven the importance of having not only network, but secure networks. So like I said, cloud is one thing, and you're moving your applications there. But with the pandemic you saw the remote work. Think about the network administrators who we're managing, hey, I've got to control network connections between my data centers, a couple clouds and maybe dozens maybe a hundred remote branches. And now I'm connecting to 10,000 micro branches that I need to ensure that they can connect up to these applications and so forth. Hell of a lot more complex environment today than it used to be for these network teams. When we look at the, what we're seeing, how the networking providers are responding it's by driving comprehensive end-to-end solutions. So unifying, wired, wireless, and WAN. Driving efficiencies there. You're seeing even ThousandEyes for Cisco and things like that. Because they know the Internet's becoming more integral part of the corporate network. So being able to drive those types of things being able to, I think look at how to drive those operational efficiencies through AI and ML. So one of the big shifts we've seen in networking is the transition to cloud-based network management. And obviously that couple of things that helps with, first of all, the operations teams who are working remotely can more easily access it. But once all that data is up in the cloud, it creates a platform to be able to invest in AI/ML, and be able to drive intelligent alerting and even automation. And that's really what's needed because as the environments get more distributed and complex, you need to have that those operational efficiencies that automation, that intelligence to help them. >> How has remote work and hybrid work affected sort of network, spending priorities. Obviously when the pandemic hit you had to accommodate end points. And I always have this theory okay, when people come back to the office and I know it's going to be a different world but, the HQ probably needs some love as well. So has that been a tailwind for the industry? >> Absolutely, that's what we're seeing now. I think when the pandemic first hit, everyone said I've got to ramp up my VPNs. I've got to scale out my concentrators. I've got to add more firewalls in my data center. And then after a while, when they realized this was here to stay, they said, okay we just created that hub-and-spoke network that we just got rid of with SD-WAN. So what are the better solutions we can implement? So now you're seeing them not only implement better networking solutions for the remote workers. But reimagining what the campus looks like. Because it's not going to be ever 100% full or maybe it will, but how, for how many times a year will it be 100% full? So you've got to go from 80% cubes and 20% conference and collaboration areas, to 80% collaboration areas and 20% cubes. So we're seeing a lot of transition taking place in the campus environment as organizations are deploying newer technologies like Wi-Fi 6E. That have greater bandwidth to allow for those collaboration apps to run in those collaboration areas. Instead of just having the single wired conference room for video. Everyone's got to be able to run their video, voice and video collaboration apps. >> So how do you look at the landscape now? Again, you can't talk about networking without talking about Cisco. I think they, up there, I saw you and Zeus as talking about out, Cisco's quarter and other networking topics. Their long term guidance is for 60% growth for a company that size that's really outstanding. I mean, Cisco's, really has always been an execution machine of course. And it's a new era now under Chuck. There are more than ankle biters. If you look at Arista's doing pretty well there's guys like Extreme, there's others that are out there but nobody seemed to be able to unseat Cisco. What's happening in the landscape? >> I mean, that's a great question. Cisco's just been around for so long and been so big for so long. And you have to also keep in mind that with Cisco it's not just about the technology, but the fact from a if you think about it from a cultural standpoint these are workers who have been trained on Cisco since, some of them since high school. The educational component that Cisco has done has groomed generations of network technologists. So when they come into the market, they're fully familiar and used to Cisco. Plus they make a really good product and they've got products that cover everything. They cover the whole gambit. So they're still able to maintain their share. They're able to grow. They're able to move. They've made a shift last year. They announced in last spring that they were going to focus more on end-to-end. So instead of just having, hey, here's a point product, here's a point product. Here's a point product. Let's think about it in its entirety. Let's deliver a complete end-to-end solution solve bigger problems for customers, which obviously makes it much harder to remove when you're just trying to remove a piece of that single problem. But the other competitors are also having good years. And I think also the rising tide floats all boats. And so because of this distributed nature, the importance of the network, everyone is doing that. Plus obviously this has to be said, the supply chain issues where people are ordering ahead as well. But organizations, you look at Arista, they've gone from just being a data center company to expanding all the way down to the campus edge, wireless, right there creating an end-to-end environment Extreme did the same thing. They went out and made a lot of acquisitions. They pulled them all together, integrated. They're all moving to this cloud based end-to-end network management. Arista has been on a tear, bringing in a lot of, not only innovative technology, but innovative technologists. So if you look at some of the organizations they bought. I keep calling it Route 128, it's 128 Technologies. So sorry folks I live in Massachusetts. It's always been Route 128. >> You Remember when don't we. 128 Technology's Mist was their big. Mist was their, Mist was kind of like their VMware. VMware to EMC was Mist was to Juniper. And so we call it the Mistification of Juniper where every organization, every company they bring in they're rolling under that and this the AI engine. So they're bringing in 128 Technologies into that. They've got their own, their own stuff under that, their wired switches. So they've got this unified wired and wireless and WAN assurance now that they have. They've been gaining a lot of traction with that. And again, for the things we were talking about because it's far more distributed and complex. You need to have, It's not like people are getting replaced. It's not like, hey, we're leveraging this automation so that we can get rid of network teams. It's because it's getting so much more complex just to have the same number of people manage that more complex environment. We need those intelligence solutions. >> So I want to ask you about network and multi-cloud. And so it's kind of tongue in cheek because we coined this term super cloud. And so what we meant by that, so here's the premise. And I wonder you could give us your perspective. Multi-cloud, I've said many times is I think largely a symptom of multi-vendor I run in this, I run in AWS or, Azure, I've done the work to understand their primitives and or Google, whatever it is. But it's not like an abstraction layer that's floating above all those but now you're starting to see that. In fact, it re:Invent in November. The ecosystem it seemed like was everybody was focused on developing what we call these super clouds. And again, it's tongue in cheek, this abstraction layer it hides the underlying complexity of the primitives and the APIs adds incremental value on top of that. So there's a company Prosimo, which Steve Herrod, is invested in and others Praveen Akkiraju, whom I'm sure you know from Viptela. Aviatrix is another company that's sort of, Steve Malaney has come on theCUBE and talked about what they're doing. Like yeah, that's super cloud. It seems like it's something new and different than just multi-cloud which is kind of connecting in to different clouds. It's that value on top. What do you think about that? And what does that mean for networking? >> That's a really good point because we are starting to see the inception of organizations going beyond having multiple cloud providers and looking at starting to deploy applications across multiple clouds. It's still really early. The vast majority of organizations are still, I use this application for this cloud and this application for that cloud. But that's the next frontier. That's what they're trying to solve is how do I create this basically cloud fabric and make it as simple as possible. And again, all the things we've been talking about how do I, instead of you having to learn Amazon, Google, Azure networking technology, learn mine, I'll take care of it, but I'll abstract all that complexity from you and make it so much simpler to be able to connect to these interconnect, and connect to them in a seamless fashion. And so that's what they're really trying to do is they're. And the hard part is it takes really sophisticated solutions to remove that high level of complexity and make it simple for an organization to do that. So yeah, absolutely. >> If I had more time I'd make it shorter as somebody who writes a lot. And I think you're right. I think it is future. It's not definitely not here today, but the other thing is it ties into digital transformation. We used this again, throw that buzzword around but, companies not just tech company, I mean everybody's becoming like a tech company, but organizations, financial services companies, healthcare they're building their own clouds on top of the hyperscalers who spend $100 billion a year on CapEx. And that seems to be a trend that I think is going to take legs over this next decade. Just like in the previous decade everybody was thinking, okay, we're going to SaaSify our business softwares (indistinct) the world. And now it's software and cloud services are the way in which I'm going to create customer experiences. >> Correct, yeah. It's why should I go out and make an investment in technology when the technology's already there? And I can rent it for when I need it scale it as I need it and, and do all of that. I agree with that. I think that's something that we're seeing. The interesting part though is that when we look at our data points, probably let than 40% of the applications and workloads are in the cloud today. So there's still a role that the corporate data center plays. We are seeing over time. They expect that to progress and transition but I think there's still always going to be maybe a quarter of the workloads and applications may never leave. Depending on how they're built, et cetera. So there's always going to be that distributed environment where you've got workloads in the private data centers, workloads in multiple public clouds. And also, the big thing too is don't forget about the edge. We're seeing a lot more edge activity take place as organizations recognize, as they deploy more IOT devices, and want to get realtime business insights they've got to deploy the compute there. >> Well, and that's something that I wanted to ask you about, but going back to what you just said, which is, I agree with you. So that suggests to me, Bob that we're just kind of, with cloud just entering the steep part of the S curve. Amazon's headed toward $100 billion, run rate business. Maybe they probably won't get there this year but they will next year. We're entering that steep growth phase, really could be. It's incredible. But I wanted to ask you about the edge. Because you're right is we got to move compute to the edge, ARM is going to dominate. I would think, the edge. They already are with our smartphones. How do you see the cloud guys participating in the edge? Whether it was Andy Jassy, or now Adam Selipsky or anybody at Amazon. They have the dogma of in the fullness of time all workloads are going to be in the cloud. So they either have to change their definition of cloud. Or they're wrong. So what's your thought on that? >> I think it really starts coming down to what's your definition of edge. And so, much like when the cloud technologies first came about and you had all the shadow IT. Everyone running off, and everyone thought oh this is all great, until you realized you had to operationalize it and you had to pull the brakes. Stop doing that. We're going to make sure IT operations. >> Call the CIO up. Exactly, finding out where stuff was by going through accounting and seeing credit card charges. For the edge what we've seen I think is maybe organizations really saying I've got to deploy my servers in my own site. Right at that edge in order to get the lowest possible latency. And so what I think we're starting to see is organizations looking at that and saying, okay well I'm in a metro and I've got 25 locations in a metro. And I've deployed technology to every single one of those sites. Do I need it there? Or can I put it in an Equinix facility that's less than five milliseconds from all 25 sites? So I think there's starting to be this pragmatic approach of looking at let's look at the edge, let's take a look at what type of latencies. What is our definition of real time. When do we actually need the data and so forth? What kind of connectivity do we have? And then from there figure out how we go about connecting it. And so for companies like AWS and Google and Azure a lot of them there's local zones and things like that. They're deploying them in those colos because they don't have data centers in every metro but they can leverage an Equinix. They can leverage someone else's hardware that's there to deploy their software stack within that location. So I think that's something that we're starting to see more and more of as the edge. And obviously the association with the telcos as well. They've got a great footprint. If you want to get close to the edge with their colos Their home offices and things like that and whatnot. Their ability to move the compute closer to the edge, the base stations of the antennas and things like that, are certainly significant. And that's why you're seeing the wavelengths and things like that, programs like that. >> So I was going to close, but there some really interesting topics you just brought up. Call it whatever you going to call it near edge, far edge or deep edge. And you mentioned real time. Yeah. So for those Equinix data centers, I don't need, true real time. But for Tesla, I need real time. I need real time inference at the edge probably using a bunch of ARM cores and I can't go back to any cloud. How do you look at that? Both, I would think big markets. Do you have a sense as to, is one bigger than the other? Are they both just enormous or we don't even know yet. >> I'm not sure that we know yet. I think certainly, it's riding the tail of the IOTs. So the more sensors, the more things that are deployed the more that, that data businesses realize they can leverage that data to make real time business insights to drive either better experiences. And if you're in retail. So location based services and real time offer management it doesn't do any good to offer a coupon for something that you've, that's 40 yards behind you. That that's past, like you said with the cars there's, I've seen some studies recently. They say, well, based on the latency, if the command is to stop and you're at one millisecond, it stops within four inches. If you are at 50 milliseconds, it stops 10 feet later. That's a big difference. And I don't know if those numbers are right but you get the idea about the impact, what the real time impact is of. >> Margin is not huge. >> Exactly, so that's where organizations, I think first and foremost need to take a pragmatic approach to determine what is real time for us. What's our definition of it. And then that can lead them to where do I need to place this compute technology? And then that goes to how do I then connect to it? So for the Teslas and so forth, obviously you're going to want 5G connections if possible. Ultra low latency and not just any 5G. The good stuff, the millimeter bandwidth stuff that that's the ultra low latency. >> So let's wrap. So, what's going on in your research world obviously the big, big acquisition tech target they seem to be investing in ESG. You guys are really growing and hiring. That's awesome. Any research that you're working on? >> Yeah, there's a couple of couple of projects we have going on right now. We're wrapping up a four part distributed cloud research series. So we did it on distributed cloud infrastructure. Applications, observability. And now this last one is on the edge. Coincidentally. So we're working on that. We've got some new network modernization research that we've published. And we're going to be looking, from a networking perspective looking at end-to-end network modernization which will be coming out soon. >> Awesome, Bob, thanks so much for coming on theCUBE. I really would love to have you back and chat about some of those things. Observability hot space. God, I wish we had more time. >> Absolutely, appreciate it, thanks. >> And thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

(upbeat music) >> Hi, everyone, welcome back to theCUBE's coverage of AWS re:Invent 2021. We're wrapping up four days of coverage, two sets. Two remote sets, one in Boston, one in Palo Alto. And really, it's a pleasure to introduce Benoit Dageville. He's the Press Co-founder of Snowflake and President of Products. Benoit, thanks for taking some time out and coming to theCUBE. >> Yeah, thank you for having me, Dave. >> You know, it's really a pleasure. We've been watching Snowflake since, maybe not 2012, but mid last decade you hit our radar. We said, "Wow, this company is going to go places." And yeah, we made that call correctly. But it's been a pleasure to sort of follow you. We've talked a little bit remotely. I kind of want to go back to some of the fundamentals. First of all, I wanted mention your earnings last night. If you guys didn't see it, again, triple digit growth, $1.8 billion RPO, cashflow actually looking pretty good. So, pretty amazing. Oh, and 173% NRR, you know, wow. And Mike Scarpelli is kind of bummed that you did so well. And I know why, right? Because it's going to be at some point, and he dials it down for the expectations and Wall Street says, "Oh, he's sandbagging." And then at some point you're actually going to meet expectations and people are going to go, "Oh, they met expectations." But anyway, he's a smart guy, he know what he's doing. (Benoit laughing) I loved it, it was so funny listening to him last night. But anyway, I want to go back to, when I talked to practitioners about data warehousing pre-cloud, they would say sound bites like, it's like a snake swallowing a basketball, they would tell me. And the other thing they said, "We just chased the chips. Every time a new Intel chip comes out, we have to bring in new servers, and we're struggling." The cloud changed all that. Your vision and Terry's vision changed all that. Maybe go back to the fundamentals of what you saw. >> Yeah, we really wanted to address what we call the data challenges. And if you remember at that time, data challenge was first of the volume of data, machine-generated data. So it was way more than just structured data, right? Machine-generated data is weblogs, and it's at petabyte scale. And there was no good solution for that type of data. Big data was not a great solution, Hadoop was really bad. And there was no good solution for that. So we thought we should do something for big data. The other aspect was concurrency, right? Everyone wants to use these data analytic platform in an enterprise, right? And you have more and more workload running against the same data, and the systems that were built were not scaling for these workloads. So you had to silo data, right? That's the only way big enterprise could deal with that, is to create many different silos, Oracle, Teradata, data mass, you would hear data mass. All of it was to afloat, right, this data? And then there was the, what do we call, data sharing. How to get access to data which is not born inside the enterprise, right? So with Terry, we wanted to solve all these challenges and we thought the only way to solve it was the cloud. And the cloud has really two free aspects. One is the elasticity, for all of a sudden, you can run every workload that you want concurrently, in parallel, on different computer resources, and you can run them against the same data. So this is kind of the data lake model, if you want. At the same time, you can, in the cloud, create a service. So you can remove complexity from users and make it really easy for new workloads to be added to the system, because you can manage, you can create a managed service, where all the sudden our customers, they don't need to manage infrastructure, they don't need to patch, they don't need to tune. Everything is done by Snowflake, the service, and they can just load in and run their query. And the third aspect is really collaboration. Is how to connect data sets together. And that's almost a new product for Snowflake, this data sharing. So we really at Snowflake was all about combining big data and data warehouse in one system in the cloud, and have only one single system where you can put all your data and all your workload. >> So you weren't necessarily trying to solve the data warehouse problem, you were trying to solve a data problem. And then it just so happened data warehouse was a logical entry point for you. >> It's really not that. Yes, we wanted to solve the data problem. And for us big data was a really important problem to solve. So from day one, Snowflake was all about machine generated data, petabyte scale, but we wanted to do it right. And for us, right was not compromising on data warehouse principle, which is a CDT of transaction, which is really fast response time, and which is also simplicity. So as I said, we wanted to solve kind of all the problems at the time of volume of data, concurrency, and these sharing aspects. >> This was 2012. You knew at that time that Hadoop wasn't going to be the answer. >> No, I mean, we were really, I mean, everyone knew that. Everyone knew Hadoop was really bad. You know, complex to manage, really slow. It had good aspects, right? This was the only system that could manage petabyte scale data sets. That's the only thing- >> Cheaply. >> Yeah, and cheaply which was good. And we wanted really to do that, plus have all the good attributes of data warehouse system. And at the same time, we wanted to build a system where if you are data warehouse customer, if you are coming from Teradata, you can migrate to Snowflake and you will get to a system which is faster than what you had on-premise, right. That's why it's pretty cool. So we wanted to do big data without compromising on data warehouse. >> So several years ago we looked at the hyperscalers and said, "Wow, last year they spent $100 billion in CapEx." And so, we started to think about this abstraction layer. And then we saw what you guys announced with the data cloud. We call it super clouds. And we see that as exactly what you're building. So that's clearly not just a data warehouse or database, it's technology that really hides the underlying complexity of all those clouds, and it allows you to have federated governance and data sharing, all those things. Can you talk about sort of how you think about that architecture? >> So for me, what I say is that really Snowflake is the worldwide web of data. And we are indeed a super cloud, or we are super-posed to the infrastructure cloud, which is our friends at Amazon, and of course, Azure, I mean, Microsoft and Google. And as any cloud, we have regions, Snowflake regions all over the world, and located on different cloud providers. At the same time, our platform is global in the sense that every region interconnects with all the other regions, this is our snow grid and data mesh, if you want. So that as an organization you can have your presence on several Snowflake region. It doesn't matter which cloud provider, so you can mix AWS with Azure. You can use our cloud like that. And indeed you can, this is a cloud where you can store your data, that's the thing that really matters, and data is structured, but it's machine structure, as I say, machine generated, petabyte scale, but there's also unstructured, right? We have added support for images, text, videos, where you can process this data in our system, and that's the workload spout. And workload, what is very important is that you can run this workload, any number of workloads. So the number of workloads is effectively unlimited with Snowflake because each workload can have its dedicated set of compute resources all operating on the same data set. And the type of workloads is also very important. It's not only about dashboards and data warehouse, it's data engineering, it's data science, it's building application. We have many of our customers who are building full-scale cloud applications on top of Snowflake. >> Yeah so the other thing, if you're not familiar with Snowflake, I don't know, maybe your head has been in the sand for a while, but separating compute and storage, I don't know if you were the first, but you were certainly the first to popularize it. And that allowed you to solve that chasing the chips problem and the swallowing the basketball, right? Because you have virtually infinite resources now at your disposal. >> Yeah, this is really the concurrency challenge that I was mentioning. Everyone wants to access the data. And of course, if everyone runs on the same set of compute resources, you have a bottleneck. So Snowflake was really about this multi-workload. We call it Multi-Cluster Shared Data Architecture. But it's not difficult to run multiple cluster if you don't have consistency of data. So how to do that while maintaining transactional property of data as CDT, right? You cannot modify data from different clusters. And when you commit, every other cluster will immediately see the change, right, as if everyone was running on the same cluster. So that was the challenge that we solve when we started Snowflake. >> Used the term data mesh. What is data mesh to Snowflake? Is it a concept, is it fabric? >> No, it's a very interesting point. As much as we like to centralize data, this becomes a bottleneck, right? When you are a large organization with different independent units, everyone wants to manage their own data and they have domain-specific expertise about that data. So having it centralized in IT is not practical. At the same time, you really want to be able to connect these different data sets together and join different data together, right? So that's the data mesh architecture. Each data set is managed independently by business owners, and then there is a contract which is exposed to others, and you can combine. And Snowflake architectures with data sharing, right. Data sharing that can happen within an organization, or across organization, allows you to connect any data with any other data on our platform. >> Yeah, so when I first heard that term, you guys using the term data mesh, I got very excited because it was kind of the data mesh is, my view, anyway, is going to be the fundamental architecture of this decade and beyond. And the principles, if I understand it correctly, you're applying the principles of Jim Octagon's data mesh within Snowflake. So decentralized data doesn't have to be physically in one place. Logically it's in the data cloud. >> It's logically decentralized, right? It's independently managed, and the reason, right, is the data that you need to use is not produced by your, even if in your company you want to centralize the data and having only one organization, let's say IT managing that, let's say, pretend. Yet you need to connect with other datasets, which is managed by other organizations. So by nature, the data that you use cannot be centralized, right? So now that you have this principle, if you have a platform where you can store all the data, wherever it is, and you can connect these data very seamlessly, then we can use that platform for your enterprise, right? To have different business units independently manage their data sets, connects these together so that as a company you have a 360 view of your customers, for example. But you can expand that outside of your enterprise and connect with data sets, which are from your vertical, for example, financial data set that you don't have in your company, or any public data set. >> And the other key principles, I think, that you've touched on really is the line of business now. Increasingly they're building data products that are creating value, and then also there's a self-service component. Assuming there's the fourth principle, governance. You got to have federated governance. And it seems like you've kind of ticked the boxes, more than tick the boxes, but engineered a solution to solve for those. >> No, it's very true. So Snowflake was really built to be really simple to use. And you're right. Our vision was, it would be more than IT, right? Who is going to use Snowflake is going now to be business unit, because you do not have to manage infrastructure. You do not have to patch. You do not have to do these things that business cannot do. You just have to load your data and run your queries, and run your applications. So now business can directly use Snowflake and create value from that. And yes, you're right, then connect that data with other data sets and to get maximum insights. >> Can you please talk about some of the things you do with AWS here at the event. I'm interested in what you're doing with your machine learning initiatives that you've recently announced, the AI piece. >> Yes, so one key aspects is data is not only about SQL, right? We started with SQL, but we expanded our platform to what we call data programmability, which is really about running program at scale across a large volume of data. And this was made popular with a programming model which was introduced by Pendal, DataFrames. Later taken by Spark, and now we have DataFrames in Snowflake, Where we are different than other systems, is that these DataFrame programs, which are in Python, or Java, or Scala, you program with data. These DataFrames are compiled to our single execution platforms. So we have one single execution platform, which is a data flow execution platform, which can run both SQL very efficiently, as I said, data warehouse speed, and also these very complex programs running Python and Java against this data. And this is a single platform. You don't need to use two different systems. >> Now so, you kind of really attack the traditional analytics base. People said, "Wow, Snowflake's really easy." Now you're injecting AI and machine intelligence. I see Databricks coming at it from the other angle. They started with machine learning, now they're sort of going after the analytics. Does there need to be a semantic layer to connect, 'cause it's the same raw data. Does there need to be a semantic layer to connect those two worlds? >> Yes, and that's what we are doing in our platform. And that's very novel to Snowflake. As I said, you interact with data in different program. You pick your program. You are a SQL programmer, use SQL. You are a Python programmer, use DataFrames with Python. It doesn't really matter. And then the semantic layer is our compiler and our processing engine, is going to translate both your program and my program in Python, your program in SQL, to the same execution platform and to the same programming language that Snowflake internally, we don't expose our programming language, but it's a data flow programming language that our execution platform executes. So at the end, we might execute exactly the same program, potentially. And that's very important because we spent all our IP and all our time, engineering time to optimize this platform, to make it the fastest platform. And we want to use that platform for any type of workloads, whether it's data programs or SQL. >> Now, you and Terry were at Oracle, so you know a lot about bench marketing. As Larry would stand up and say, "We killed the competition." You guys are probably behind it, right. So you know all about that. >> We are very behind it. >> So you know a lot about that. I've had some experience, I'm not a technologist, but I'm an observer and analyst. You have to take benchmarking with a very big grain of salt. So you guys have generally stayed away from that. Databricks came out and they came up with all these benchmarks. So you had to respond, because otherwise it's out there. Now you reran the benchmarks, you took out the materialized views and all the expensive stuff that they included in your cost, your price performance, but then you wrote, I thought, a very cogent blog. Maybe you could talk about sort of why you did that and your general philosophy around bench marketing. >> Yeah, from day one, with Terry we say never again we will participate in this really stupid benchmark war, because it's really not in the interest of customers. And we have been really at the frontline of that war with Terry, both of us, really doing special tricks, right? And optimizing this query to death, this query that no one runs apart from the synthetic benchmark. We optimize them to death to have the best number when we were at Oracle. And we decided that this is really not helping customers in the end. So we said, with Snowflake, we'll not do that. And actually, we are not the only one not to do that. If you look at who has published TPC-DS, you will see no one, none of the big vendors. It's not because they cannot run TPC-DS, Oracle can run it, I know that. And all the other big data warehouse vendor can, but it's something of a little bit of past. And TPC was really important at some point, and is not really relevant now. So we are not going to compete. And that's what we said is basically now our blog. We are not interesting in participating in this war. We want to invest our engineering effort and our IP in solving real world issues and performance issues that we have. And we want to improve our engine for these real world customers. And the nice thing with Snowflake, because it's a service, we see exactly all the queries that our customers are executing. So we know where we are struggling as a system, and that's where we want to invest and we want to improve. And if you look at many announcements that we made, it's all about under-the-cover improving Snowflake and getting the benefit of this improvement to our customer. So that was the message of that blog. And yes, the message was okay. Mr. Databricks, it's nice, and it's perfect that, I mean, everyone makes a decision, right? We made the decision not to participate. Databricks made another decision, which is very fine, and that's fine that they publish their number on their system. Where it is not fine is that they published number using Snowflake and misrepresenting our performance. And that's what we wanted also to correct. >> Yeah, well, thank you for going into that. I know it's, look, leaders don't necessarily have to get involved in that mudslide. (crosstalk) Enough said about that, so that's cool. I want to ask you, I interviewed Frank last spring, right after the lockdown, he was kind enough to come on virtually, and I asked him about on-prem. And he was, you know Frank, he doesn't mix words, He said, "We're not getting into a halfway house. That's not going to happen." And of course, you really can't do what you do on-prem. You can't separate compute, some have tried, but it's not the same. But at the same time that you see like Andreessen comes out with this blog that says a huge portion of your cost of goods sold is going to be the cloud, so you're going to have to repatriate. Help me square that circle. Is it cloud forever? Is it will you never say never? What can you share of that? >> I will never say never, it's not my style. I always say you can always change your mind, and maybe different factors can change your mind. What was true at some point might not be true at a later point. But as of now, I don't see any reason for us to go on-premise. As you mentioned at the beginning, right, Snowflake is growing like crazy. The world is moving to the cloud. I think maybe it goes both ways, but I would say 90% or 99% of the world is moving to the cloud. Maybe 1% is coming back for some very specific reasons. I don't think that the world is going to move back on-premise. So in the end we might miss a small percentage of the workload that will stay on-premise and that's okay. >> And as well, if you dig into some of the financial statements you'll see, read the notes where you've renegotiated, right? We're talking big numbers. Hundreds and hundreds of millions of dollars of cost reduction, actually more, over a 10 year period. Billions of your cloud bills. So the cloud suppliers, they don't want to lose you as a customer, right? You're one of their biggest customer. So it's awesome. Last question is kind of, your work now is to really drive the data cloud, get adoption up, build that supercloud, we call it. Maybe you could talk a little bit about how you see the future. >> The future is really broadened, the scope of Snowflake, and really, I would say the marketplace, and data sharing, and services, which are directly built natively on Snowflake and are shared through our platform, and can operate, it can mix data on provider-side with data on consumer-side, and creating this collaboration within the Snowflake data cloud, I think is really the future. And we are really only scratching the surface of that. And you can see the enthusiasm of Snowflake data cloud and vertical industry We have nuanced the final show data cloud. Industry, complete vertical industry, latching on that concept and collaborating via Snowflake, which was not possible before. And I think you talked about machine learning, for example. Machine learning, collaboration through machine learning, the ones who are building this advanced model might not be the same as the one who are consuming this model, right? It might be this collaboration between expertise and consumer of that expertise. So we are really at the beginning of this interconnected world. And to me the world wide web of data that we are creating is really going to be amazing. And it's all about connecting. >> And I'm glad you mentioned the ecosystem. I didn't give enough attention to that. Because as a cloud provider, which essentially you are, you've got to have a strong ecosystem. That's a hallmark of cloud. And then the other, vertical, that we didn't touch on, is media and entertainment. A lot of direct-to-consumer. I think healthcare is going to be a huge vertical for you guys. All right we got to go, Terry. Thanks so much for coming on "theCUBE." I really appreciate you. >> Thanks, Dave. >> And thank you for watching. This a wrap from AWS re:Invent 2021. "theCUBE," the leader in global tech coverage. We'll see you next time. (upbeat music)

(upbeat music) >> Welcome back to Las Vegas. theCUBE is here, live at AWS re:Invent 2021. Lisa Martin with Dave Nicholson. theCUBE has two sets today, two, not one, two, two live sets, two remote sets, over 100 guests on the program at this event, it's a lot, talking about the next generation of cloud innovation with AWS and its massive ecosystem of partners and we are pleased to welcome Walton Smith to the program, the public sector, director of strategic partnerships for Worldwide Technology, Walton welcome to the program. >> Thank you so much for having me, it's really amazing to be here and look forward to a great conversation. Isn't it great to be in person again? >> It's so nice to be in person, I mean I'm glad everybody's being safe and, and checking vaccine status and whatnot, but it's good to get back and, and, and work with people cause we can really drive innovation when, when we get together. >> Those hallway conversations or those conversations here at events that you just can't replicate by video conferencing, right? Not replicate that, you getting grabbed in the hall and say, hey, have you thought about leveraging XYZ to do something? To me that's what makes this conference great. >> Talk to me about what's going on at WWT. What are some of the, the things that you guys have been working on? >> It's a really exciting time at Worldwide, we're really working closely with AWS to drive innovation to the edge. We're excited about their outpost offering, we actually have one in our data center, Sandy announced it today in a partnership with Intel to, to allow our customers to try to work out use cases, to, to kick the tires, so to speak, to see how it works as well as our partners to get their ISV products certified on the outpost platform. >> So I'm familiar with your ATC in St. Louis, is that what you're referring to? >> That's correct. >> Give us a little, give us a little insight into what goes on there, I know it's pretty amazing from a customer perspective because you are agnostic. because you are agnostic. >> Walton: Correct. >> You're there to serve the customer, but tell me, tell me what happens in the ATC. >> We say we're agnostic, but we have our, our, our preferences because we know- >> sure, sure, okay. what actually works. But our ATC is our crown jewel, it's about a $600 million data center that we built solely for proof of concepts for our customers. So our, our top customers come in and say, I have this problem, how can I solve it? And so with us being the single biggest reseller of just about every ISV is out there, I can stand up a, a, a Dell, I can stand up a, a, a Dell, Dell compute next to NetApp storage with Cisco router on top of it to replicate what my customer has at the VA, for example, and then to be able to plug in an outpost to show how leveraging the outpost can give them a single pane of glass to be able to work on their workload, so the training that our FSI, Federal System Integrators have put into their staff or our government customers on the Amazon platform can now be driven into their data center, so it's really taking the cloud down to where the data is. >> In terms of public sector, what are some of the prominent use cases that you guys are helping customers to solve, especially given the tumultuous times that we're still living in? Sure, so what we saw during COVID especially was how most of the government agencies had the capability to allow say 5% to 10% of their workforce to work remotely. And then with COVID, they went to 95% to a 100% workforce. So, a lot of the time we've spent over the last year is how do we securely allow our government employees to get access to the information, because as we know, the government was more valuable than ever to get us through this pandemic, we had to give them the tools that they needed to be able to make the decisions to, to move the country forward. >> Talk about security if you will for a second, we have seen such a dramatic change in the security landscape, the threat landscape, ransomware as a service, it's, you know, the cyber criminals, lot of money in it, they're becoming far more brazen. What are some of the things that you're seeing specifically with respect to security use cases? >> It's, it's gone from, let me just buy everything that's out there and that'll give me security to, I need to have visibility into my environment, because if, if you look at target, it's a great case studies around that, they had all the tools, they just didn't tie it all together. And so as more and more nation state actors And so as more and more nation state actors try to attack our government, or it's a great way to make money, I mean, in, in this, in the presentation, Sandy's today, they talked about, if you looked at the GDP of what's been taken in ransomware, it's like the 10th biggest country in the world, I mean, it's scary and staggering how much money is lost. So what we think, going back to our ATC, we can stand up their environment, we can work with the top security providers in the world to show those customers how we can give them that visibility, the, the, the protection and the ability to get back up, because there's really only two types of organizations, those who've been hacked and those who don't know they've been hacked, they're going to get in, it's how do we mitigate the damage, how do we get them back up and running and how we protect my customers or have some of the most sensitive data in the world, how do we protect that so our government can keep us safe and keep us moving forward. >> Yeah, cause these days it's a matter of when we get hacked, not if. And of course we are only hearing about the large attacks. >> Walton: Correct. We don't hear about- all of the ones that go on day in and day out, I think, I think I saw a stat recently that a ransomware attack happens like once every 11 seconds. >> Correct, I mean, just walking through here, how many text messages you've gotten? You want a free iPad click here, I mean, they're, they're down to the individual level. It's a whole lot cheaper to give a couple people, really powerful laptops, pizza and beer, and have them go attack, than it is to, to set up a real business and so, unfortunately, as long as there's money in it, there's going to be bad actors out there. We think partnering with AWS and other partners can help build solutions. >> You know, WWT has had an interesting history because you didn't start with the dawn of cloud. >> Walton: Right. So you've been in the business of AT for a long time So you've been in the business of AT for a long time and logistics out of St. Louis in a lot of ways. What does that look like in terms of navigating that divide? You know, there's a, there's a whole storied history of companies that were not able to cross the divide from the mainframe era to the client server era, let alone to cloud. You seem to have, you seem to be doing that pretty well. >> I, I appreciate that, I mean, we're the biggest company no one's ever heard of. We're 14, $15 billion privately held firm, the same two guys that founded it, still run it today and all they want to do is do cool things, they want it to be truly the best place to work. So from day one, they've invested in training our staff, building the ATC to give us the tools we need to be successful and then because we're a trusted partner with Amazon Intel and our other partners out there, they're investing in us to help build solutions, so we have over 6,000 engineers, they get up every day, how do I build something that can help our customers really drive change and innovation? So it's been a really fun ride and the, the best is yet to come. >> Talk to me about your customer focus, you know, when we talk, here we are at reinvent, we always talk with AWS about their, you know, Dave, we talked about this customer obsession, the fact that they're working backwards from the customer, do you share that sort of philosophy? Does WWT share that philosophy with AWS? >> 100%?, if you go to WWT.com we've published everything that we have so you can get full access to our lab to learn about x ISV and go deep to learn about x ISV and go deep and see the million and a half labs we've built around, say Red Hat and go and get access to it. So we think that if we educate our customers, there are going to be customers for life, and they're going to come to us with their biggest problems. And that what's, is what's exciting and what enables us to, to really continue to grow. >> And how did the customers help you innovate? And that's one of the things we, I was thinking yesterday with, with this AWS flywheel of when Adam was introducing, and now we have a, now we have, and it was because he would say, we did this, but you needed more, but you being the customer needed more. >> 100%, it, it's we want our customers to come to us with their biggest problems, because that's when we, the exciting innovation works. And so the ability to sit down with the foremost expert in, in virus control and be able to, in, in virus control and be able to, what are the tools that she need to be able to get ahead of the next change to COVID? How can we give them the tools to do that? That's what we want to do, the scalability, the ability to reach out to others is what Amazon brings. So we can bring the data science, we can bring the understanding of the storage, the security, and the network and then AWS gives that limitless scalability to solve those problems and to bring in someone from Africa, to bring in someone from the European Union to, to work together to solve those problems, that's what's, what's exciting and then coming back to the outpost, to be able to put that in the data center, we know the data center is better than just about anybody out there, so it would be the ability to add innovation to them, to bring those part ISV partners together. It's really exciting that Intel is funding it because they know that if, if customers can see the art of the possible, they're going to push that innovation. >> One of the things we've also sort of thematically Dave and I with guests, and the other has been talking about this week is that every company has to be a data company, whether it's public sector, private sector, if you're not, or if you're not on your way, there's a competitor right here in the rear view mirror ready to take your place. How do you help public sector organizations really develop, embrace an execute a data full course strategy? >> So we have a cadre of over 125 data scientists that work every day to help organizations unlock their most valuable asset, that data, their people and be able to put the data in the right place at the right time and so by investing in those data scientists, investing in the networking folks to be able to look at the holistic picture is how we can bring those solutions to our customers, because the data is the new oil of, of the environment and sorry for my Southern twang on the oil, but it, but it truly is the most valuable asset they have and so, how do we unlock that? How do they pull that data together, secure it? Because now that you're aggregating all that data, you're making it a treasure trove for those bad actors that are out there, so you've got to secure it, but then to be able to learn and, and automate based on, on what you learned from that data. >> You know I, I think with hindsight, it's easy to, it's easy to say, well, of course WWT is where WWT is today. Five years ago, though, I think it would have been an honest question to ask, how are you going to survive in the world of cloud? And here we are, you've got outposts. >> Walton: Sure. >> And, and of course it makes sense because you're focused on customers, sounds like I'm doing a commercial for you, But I'm a fan- >> I'll gladly apreciate that- because I, I, I've worked with you guys in a variety of roles for a long time, seems like yesterday we were testing a bunch of different storage arrays of the ATC and now you've got outposts in cloud and you're integrating it together. It's really more of the same, I'm sure if we had your founders here, they'd tell you, Dave, it's all the same. >> Walton: Correct. It's all the same. >> It's AT, it's where, where's the compute, where's the storage, how do you get access to it and the cloud has given the ability to, to scale and do things you could never imagine. I think it's the reason we're here is because our leadership continues to invest and pushing that envelope to give people the freedom to go out with that crazy idea, what if we did this? And having the tools and the ability to do that is, is what, what drives our innovation and that's what we bring to our customers and our partners, that ability to innovate to, that ability to innovate to, to tackle that next problem. >> So what's the tip of the spear right now for you guys? What are you, what's, what's, what's kind of, what's next? What are you waiting to have delivered to the ATC to racket, stack and cable up? >> Lot's of stuff that I can't tell you about because there, there's things that Amazon is, is always working on that we work with before it, it's, it's made public, so there's a lot of really cool stuff in the pipeline, because the, as you think about moving to the data center, that's one thing, moving to truly to the edge, where you can help that war fighter, where you can help that mission, where you can do disaster recovery, leveraging the snowball family, the outpost family, and custom built tools that really allow for quick response and custom built tools that really allow for quick response to whatever that problem is, is that next front and that's where we've been for a long time, helping our, our war fighters and folks do what needs to be done. Outpost sees that you can leverage big AWS Outpost sees that you can leverage big AWS to build the models, push it down to the edge because you don't have time or the bandwidth to get it back into the big cloud, to be able to put that compute and storage and analytics on the edge to make real time decisions, is what we have to do to stay relevant and that's where the joint partnership is really exciting. >> It's what you have to do to stay relevant, it's also what your customers need, cause one of the things that we've learned in the pandemic is that real-time data and access to it is no longer, longer a nice to have, this is business critical for everything. >> Correct and even if you have a fat pipe to get it, you need to make real time decisions and if you're in a really sandy space, excuse me, making hard decisions, you've got to get the best information to that soldier when, when they need it to, to save our lives or to save the other people's lives so it's, it's, it's not just a nice to have, it's mission critical. >> It is mission critical, Walton, thank you so much, we're out of time, but thank you for joining Dave and me talking about- >> Really enjoyed it. all the stuff going on with, with worldwide, the partnership with AWS, how you're helping really transform the public sector, we appreciate your time and your insights. >> Thank you so much, have a great conference. >> Thanks, you too. >> Okay, thanks. >> All right, from my buddy, Dave Nicholson, I'm Lisa Martin, you're watching theCUBE, the global leader in live tech coverage. (upbeat music)

>>Here you are new. Welcome back to the cubes. Continuing coverage of AWS reinvent 2021 live from Las Vegas. Lisa Martin, with John farrier, John, we have two live sets. There's a dueling set right across from us two remote studios over 100 guests on the cube at AWS reinvent 2021. Been great. We've had great conversations. We're talking about the next generation of cloud innovation and we're pleased to welcome one of our alumni back to the program. Lisa Bernays here, the CEO and co-founder of D L Z P group. Lisa. Welcome. >>Hi, thank you. I appreciate the opportunity to be here with you and John. It's a great opportunity >>And John's lucky he gets to lease us for the price of London. One second. Talk to me about da DLDP. This is a woman and minority owned company. Congratulations. That's awesome. But talk to us about your organization and then we'll kind of dig into your partnership with AWS. >>Sure. So DLC P group, we found it in 2012. Um, and for us, we were at the time we were just looking for a way to offer a value added service to our customers. We wanted to always make sure that we were giving them the best quality, but what I also wanted to do is I wanted to create an environment for my employees, where they felt valued, and we kind of built these core values back then about respect, flat hierarchy, um, team, team learning, mentorship, and we incorporated, so everybody can do this remotely from around the world. So we've always made sure that our employees and customers are getting the best value. >>Well, what kind of customers, what target market, what kind of customers do you guys work with? >>Well, we've actually made sure that we're diverse. We make sure that we have 50% in public sector and 50% in private sector, but it's been very, very interesting journey for us because once we started one sec, like we started with cities and then a number of cities started contacting us to do more business. So it's always been this hurdle to make sure we're diverse enough to make sure we offer the best solutions. >>And you jumped in with AWS back in 2012 when most folks were still to your point. I saw your interview earlier this summer, thinking about Amazon as a bookstore, why a debit? What did you see as the opportunity back in 2012 with them? >>Well, when we first heard about AWS, my first thought is, well, it's amazon.com. What is AWS? And then once we started talking to them, we saw the capabilities and the potential there. We saw what it could do. So we partnered with them to actually have the first working PeopleSoft customer on AWS. So that's a large ERP application and that helped build the foundation to prove what could actually run on the cloud. And since then, we've been able to prove so much more about the technology and what AWS is accomplishing. >>Was it a hard sell back in the day? >>It was a little bit hard, but it was interesting because we were speaking with one of our customers they're on premise and they're like, well, you know, we're going to have to re do a whole data center. We're talking about millions of dollars. We don't really have the budget to redo this. And that's when we're like, well, we have this great partnership with Amazon. We think this would be the perfect opportunity to let you try the cloud and see how successful it was. >>At least I want to point out you got your, one of the Pathfinders that Adams Leschi pointed out because back in 2012, getting PeopleSoft onto the cloud, which is really big effort, but that's what everyone's doing now. I just saw the news here. SAP is running their application on graviton too, right? So you start to see and public sector during the pandemic, we saw a ton of connect. So you were really on this whole ERP. ERP is our big applications. It's not small, but now it's, everyone's kind of going that way. What's the current, uh, you feel how you feel about that one? And what's the current update relative to the kind of projects you got going on? >>Well, we've, we've evolved quite a bit. I mean, PeopleSoft is always going to be in our DNA. A lot of my employees are ex or Oracle employees. They have developed a lot of the foundations for PeopleSoft, but since then, like we've worked with serverless technology when that was released a number of years ago, we, we asked our team, okay, AWS just talked about Lambda, serverless technology, go figure out what is the best solution. We ended up running ours, our website serverless. We were one of the first. And from that, we brought our website costs down from hundreds of dollars to pennies a month. So it's a huge savings. And then we started, um, about two years ago, we spoke with our utility company. Um, there were saying how with machine learning, they were only going to be able to get a 75% accuracy for their wind turbines. And we said, well, let us take a shot at it. We have some great solutions on AWS that we think might work. We were able to redo their algorithm using AWS cloud native tools, open source data to get a 97 to 99% accuracy on a daily basis. And that saves them millions of dollars each day. >>Don's right. And as Adam was saying with some of the folks, customers, he was highlighting on main stage the other day, you are a Pathfinder. How did you get the confidence? Especially as a female minority owned business. I'd love to just get maybe for some of those younger viewers out there. How did you get the confidence to, you know what? I think we can do this. >>I think for me, I, I, I don't like to take no for an answer. There's always a solution. So we're always looking at technology, seeing how we can use it to get a better answer. >>What do you think about reinvent this year? A lot of goodies here every year, there's always new creative juices flowing because it's a learning conference, but it's also feels like a futuristic kind of conference. What's your take this year? >>I don't know if you happen to attend midnight madness when they were talking about robotics and the future with that. I mean, we've been talking about that for a number of years of what could be created with robotics. Like even my son back in middle school was talking about creating a robot Butler. He just, everybody knows what the future is. And it's so great that we finally have the foundation in technology to be able to create these >>Well, if you're someone that doesn't like to say, no, does your son actually have a robot Butler these >>Days? He's still working on it. >>That's a good answer to say, Hey, sorry, your mom's not going to be there to get the robot. The latency thing. This is the robot. First of all, we'd love the robotics, I think is huge. We just had George on who's the fraught PM for ECE to edge and late, the wavelength stuff looks really promising for the robotics stuff. Super exciting. >>Yes. We can't wait to start playing with it more. I mean, it's something that our team has been dabbling. We spent probably about 30% of our time on R and D. So we're looking at the future and what we can invent next because >>You guys can affect such dramatic changes for customers. You talked about that wind turbine customer going from 75% accuracy to 97, 90 8%. Where are your customer conversations? Cause that's, is, are they at the C level with showing organizations that dramatic reduction in costs and workforce productivity increased that they can get? >>We talk with everyone it's it could be the solution architect. It could be an intern. It could, and we're just sharing our ideas with them. And we also talk with the C level. Um, it's just, it's everybody is interested in and they have different, different ideas that they want to share. So with the solution architect, we can share with them the code and how we're going to architect it. While the C level, we just pointed out black and white, this is your cost. Now this is what your cost is going to be. And everybody is happy. They, they jump on board with it. >>Lisa, you mentioned 30% R and D by the way, it's awesome. By the way, that's well above most averages, what are you working on? Because I totally think companies should have a big R and D play around budget, get a sandbox, going get some tinkering. Cause you never know where the real discoveries we had. David Brown who runs NC to nitro, came out of a card on the network. So you'd never know where the next innovation comes from. What's the, what are you guys doing for R and D? What's the fun projects are what endeavors. >>So there's two of them. One is actually a product, which is a little bit out of our comfort zone, but we're, we're, we're looking to develop something that will be able to help, um, NASA. So that's the goal where, you know, we've been working on it since they released their ma their mission to Mars projection. So it's something that we're very passionate about, but then we're also building a software. Uh, we've been working on it for about three years now and we actually have two customers prototyping it. So we're hoping to be able to launch it to the public within the next year. >>You mentioned NASA and I just about jumped out of my chair. That was my first job out of grad school was really the space program. Can you tell us a little bit more about what you're helping them do? I love how forward-thinking that they are, obviously they always have been, but tell me a little bit more about that. >>So I can't share too much because it's one of those things is a common sense thing. Once you think about a little bit more, it's kind of like why didn't anybody never think about this? So we're using new technology and old technology together to combine the solution. >>Ooh, I can't wait to learn more. Talk to us about these. Think big for small business TB SB program at AWS. How long have you guys been a part of that and what is it enabling? What is it going to enable you to do in 2022? So >>The think big for small business program was the brainchild is Sandy Carter. And I am always, always going to be grateful to her. Um, I met with her in 2019. I shared her journey, our journey with her about how we started out being a premier partner and then over time, because there's so many other partners, we were downgraded. And because just because we're a small business, and even if I had every employee, even my admin staff certified, we would never have enough employees to be to the next level, even though we had the customers, the references. So she listened to us and other small businesses and created the program. And it's been a great opportunity for us because we're, we're gaining access to capital, you know, funding for opportunities. We're getting resources for training. So it, for us, it's been a huge advantage. >>It sounds like a part of that AWS flywheel that we always talk about. John Sandy Carter being one of our famous Cuba alumni. She was just on yesterday with you. Okay. >>And there's so many opportunities for all businesses because you can, you can tackle these problems. You don't have to be a large partner. You can have specialty in AI works really well in these specialized environments. And even technically single-threaded multithreaded applications, which is a technical CS term is actually better to have a single threaded. If you have too many cores, it's actually bad technically. So the world's changing like big time on how technology. So I'm a huge fan of the program. And I think like it's just one of those things where people can get it from cloud and be successful. >>Yes. And that's the goal. I mean, there is so much opportunity in the cloud and we bring interns on all the time, just so they can learn. And what, what resonated with me the most was we brought a high school senior in, he goes, I was with you guys for three months. I learned more in three months, I did four years of high school. And he's like, you set me up for the future. >>Oh my gosh. If there's not validation for you doing in that statement alone. My goodness. Well, you know, some of the things that, that are so many exciting announcements that have come out of this reinvent, so great to be back in person one. Um, but also, you know, being able to help AWS customers become data companies. Because as we were been talking about the last couple of days, every company has to be a data company. You gotta figure it out. If you're, if you haven't by now, there's a competitor right back here, who's ready to take your spot. Talk to us about what excites you about enabling companies to become data companies as we head into 2020. >>Well, for us, everybody has so much data nowadays. You know, I mean even think about cell phones, how much data is stored in that. So each device has so much information, but what do you do with it? So it's great because a lot of these companies are trying to figure out what, how can we use this data to prove that improve the experience for our customers? So that's where we've been coming in and showing them, okay, well, you can take that data. You look at Lisa and John cell phone. You see that they, they love to look up where they're going to go on their next vacation. You can start creating algorithms to make sure that they get the best experience one for the next vacation to make sure it's not a won't Rob the bank. >>Awesome. And going on vacation tomorrow. So I'll be, I'll be expecting some help from you on that. It's been great to have you on the program. Yeah. Congratulations on the success, the partnership, and where can folks go if if young or old years are watching and are interested in working with you, it's the website where they, where can they go to learn more >>Information? So they can go to D L Z P group.com >>DLZ P group.com. Awesome. Lisa, thanks so much for coming back on the program. Great >>To see you. Thank you so much. All >>Right. For John furrier, I'm Lisa Martin and you're watching the cube, the global leader in live tech coverage.

(bright upbeat music) >> Welcome back to theCube's coverage of AWS re:Invent 2021. This is "theCube". We go out to the events. We extract the signal from the noise. We're here at a live event, hybrid event, two sets. We had two remote studios prior to the event, over 100 interviews. Really excited to have George Elissaios here. He's the director of product management for EC2 Edge, really interesting topic at AWS. George, great to see you. Thanks for coming on. >> Yeah, great to be here. Thanks for having me. >> So, everybody's talking about Edge, IoT, EC2. What's the scope of your portfolio, your responsibility? >> Yeah, well, our vision here at AWS is to really bring the power of the AWS platform wherever customers need it. AWS wherever our customers want it is our long-term vision. And we have a bunch of products in this space that help us do that and help us enable our customers whatever their use case is. So we have things like Wavelength. I know we talked about Wavelength before here in "theCube", where we bring full AWS service at the edge of the 5G network, so with 5G edge computing in partnership with telcos worldwide, our partnership with Verizon in the US has been flourishing. We're up to, I think, 15 or more Wavelength zones right now in many of the major cities in the US, but also in Japan and Korea, and in Europe with Vodafone. So that's one of the portfolio kind of offerings. And that helps you as a customer of AWS if you want to have the best latency to mobile devices, whether they are sensors, or mobile phones, or what have you. But we're also feeling out that Edge portfolio with local zones. Earlier today in Werner's keynote, we announced that we're going to launch another 30 local zones in 20 new countries, everywhere from South America, Africa, Asia, Australia, and Europe, obviously. So a lot of expansion there. Very excited about that. And that is kind of a similar offering, but it basically brings you closer to customers in metropolitan areas over the internet. >> So, Wavelength's a big feature. George, I want to get just to touch on it because I think latency comes up a lot in Edge conversations, low latency issues, whether it's cars, factories. You guys gave a demo yesterday to the press corps in the press room, I was there, where you had someone in San Francisco from the Opera and someone in person here in Vegas, and you had 13 milliseconds going back and forth demoing, real time- >> Collaboration. >> The benefit of low latency in remote. It wasn't next door. It was San Francisco. This is kind of the purpose of what Edge is about. Can you explain what that means, that demo, why it was important, and what you were trying to show, and how does it mean for the Edge? >> So there is multiple use cases. One of them is human collaboration, right? Like, we spent the last two years of our lives over conferences and kind of like the teleconferences, and trying to talk over each other and unmute ourselves desperately. But existing solutions kind of work, generally, for most of the things that we do, but when it comes to music collaboration where milliseconds matter, it's a lot harder with existing solutions to get artists to collaborate when they're hundreds of miles away. Last night, we saw a really inspiring demo, I think, of how two top tier musicians, one located in San Francisco and one located in Vegas, can collaborate in opera, which is one of the most precise art forms in the music world. There are no beats in opera to kind of synchronize, so you really need to play off each other, right? So we provided a latency between them of less than 30 milliseconds, which translates, if you're thinking about audio or if you're thinking about the speed of sound, that's like being in the same stage. And that was very inspiring. But there's also a lot of use cases that are machine to machine communications, where even lower latencies matter, and we can think of latencies down to one millisecond, like single digit milliseconds when it comes to, for example, vehicles or robots, and things like that. So we're, with our products, we're enabling customers to drive down that latency, but also the jitter, which is the variation of latency. Especially in human communications, that is almost more important than latency itself. Your mind can adapt to latency, and you can start predicting what's going to happen, but if I'm keep changing that for you, that becomes even harder. >> Well, this is what I want to get to because you got outcomes and applications like this opera example. That's an application, I guess. So working backwards from the application, that's one thing, but now people are really starting to trying to figure out, "What is the Edge?" So I have to ask you, what is AWS's Edge? Is it Outpost, Wavelength? What do people buy to make the Edge work? >> Well, for us, is providing a breadth of services that our customers can either use holistically or combine multiple of those. So a really good example, for example, is DISH Wireless. I'm sure you know we're building with DISH the first in the world mobile network, 5G mobile network fully on cloud, right? So these combines Outposts and combines local zones in order to distribute the 5G network across nationwide. And different parts of their applications live in different edges, right? The local zone, the Outputs, and the region itself. So we have our customers... You know, I talked about how local zones is going to be, you know, in total, 45 cities in the world, right? We're already in 15 in the U.S. We're going to do another 30. But customers might still come, and say, "Oh, why are you not," you know, "in "in Costa Rica?" Well, we'll have Outposts in Costa Rica. So you could build your own offering there, or you could build on top of Outputs while you distribute the rest of your workload in existing AWS offering. So to answer your question, John, there is no single answer. I think that it is per use case and per workload that customers are going to combine or choose which one of- >> Okay, so let's go through local zones. Explain what a local zone is real quick. I know we covered it a bit last year with the virtual event, but local zones are now part of the nomenclature of the AWS language. >> Yes. >> And we know what a region is, right? So regions are regions. What's a local zone? >> When your region's saying new availability zones, and then we're just (chuckles)- >> You got availability zones. Now you got local zones. Take us through the topology, if you will, of how to think about this. >> Right, so a local zone is a fully-managed AWS infrastructure deployment. So it's owned and managed and operated by AWS. And because of that, it offers you the same elasticity, and security, and all of the goodies of the cloud, but it's positioned closer to your end customers or to your own deployment. So it's positioned in the local urban, metropolitan or industrial center closer to you. So if you think about the U.S., for example, we have a few regions, like, in the East Coast and in the West Coast, but now, we're basically extending these regions, and we're bringing more and more services to 15 cities. So if you are in Miami, there is a local zone there. If you are in LA, there is two locals zones actually in LA. That enables customers to run two different types of workloads. One is these distributed clouds or distributed Edge kind of workload that we've been hearing more and more about. Think of gaming, for example, right? Like, we have customers that are, like Supercell, that need to be closer to the gamers, wherever they are. So they're going to be using a bunch of local zones to deploy. And also, we have these hyper-local use cases, where we're talking, for example, about Netflix that are enabling in LA their creative artists to connect locally and get like as low as single millisecond latencies. So local zone is like an availability zone, but it's closer to you. It offers the same scalability, the same elasticity, the same security and the same services as the AWS cloud. And it connects back to the regions to offer you the full breadth of the platform. >> So just to clarify, so the Edge strategy essentially is to bring the cloud, AWS, the primitives, the APIs, to where the customers are in instances where they either can't move or won't move their resources into the cloud, or there's no connectivity? >> Right, we have a bunch of use cases where customers either need to be there because of regulation or because of some data gravity, so data is being generated in a specific place and you need to locally process it, or we'll have customers in this distributed use case. But I think that you're pointing out a very important thing, which is a common factor across all of these offerings. It's it is the cloud. It's not like a copycat of the cloud. It's the same API. It's the same services that you already know and use, et cetera. So extending the cloud rather than copying it around is our vision, and getting those customers who, well, connectivity obviously needs to be there. We were offering AWS Private 5G. We talked about it yesterday. >> Now, a premise that we've had is that a lot of Edge use cases will be driven by AI inferencing. And so... First of all, is that a reasonable premise, that's growing, we think, very quickly, and it has huge potential. What does the compute, if that's the correct premise, what does the compute look like for that type of workload? >> That is a great premise, and that's why we think that the model that we're offering is so powerful, because you have the Edge and the cloud fully cooperating and being connected together. You know, the Edge is a resource that's more limited than the full cloud in the AWS region. So when you're doing inferencing, what you really want to do is you want to train your models back up in the region where you get more scalability and the best prices. You know, you have the full scale of AWS. But for the latency-sensitive parts of your applications, you want to push those to the Edge. So when you're doing the actual inferencing, not the training of the models- >> Real time. Yeah. >> Real time, you push that to the Edge, whether that's if your connectivity is 5G, you can push that into a Wavelength zone. If your connectivity is wired, you can push it into a local zone. If you really need it to be in your data center, you can push it in your Outposts. So you see how our kind of like building out for all of those use cases. >> But in those instances, I'm interested in what the compute looks like, 'cause I presume it's got to be low power, low cost, super high performance. I mean, all of those things that are good for data-driven workloads. >> Right, the power, if we think here, is the same compute that you know and love in the cloud. So the same EC2 instance types, the EBS volumes, the S3 for storage, or RDS for your databases and EMR clusters. You can use the same service. And the compute is the same powerful all the way down from the hardware up to the service. >> And is the promise to customers that eventually those... It's not all of those services, right? I mean, you go to Outposts today, it continues to grow. >> Continuing to grow, yeah. Right, so but conceptually, as many services you could possibly push to the Edge, you intend to do so? >> We are pushing services according to customer requests, but also there is a nuance here. The nuance is that you push down the services that are truly latency-sensitive. You don't need to push everything down to the Edge when you're talking about latency- >> Like, what's an example of what you wouldn't push down? >> So management tools, right? So when you're doing monitoring and management, yeah, you don't need these to be at the Edge. You can do that, and you can scale that. Or, you know, batch processing, it doesn't have to be at the Edge because it's, by definition, not online, not like a latency service. So we're keeping those, like AWS Batch, for example, that's in the region because, you know, that's where customers really use it. But things like EC2, EBS, EMR, we're pushing those to the Edge because those are more- >> We got two minutes left. I want to get the Outposts kind of update. I remember when Outposts launched. It was really a seminal moment for re:Invent. Hybrid. "Oh, Andy Jassy said hybrid." Yeah. "I'll never say hybrid." But now hybrid's kind of translated into all cloud operations. Now you got local zones. A lot's changed from Amazon Web Services standpoint since Outposts launched. Local zones, things are happening. 5G, DISH. Now what's the status of Outposts? Are you guys happy with it? What has it morphed into? Is it still the same game? What is Outposts today, vis-a-vis what people may think it is or isn't? >> Yeah, we've been focusing in what we're talking about, building out a number of services that customers request, but also being in more and more places. So I think we're in more than 60, now, countries with Outposts. We've seen very good adoption. We've seen very good feedback. You know, half of my EBCs have been on Outposts, but this year, I think that one of the most exciting announcements were the Outposts servers. So the smaller form factors that enable an additional use cases, like for example, retail or even building your 5G networks. You know, one of our partners, Mavenir, is moving their 5G core, so the smarts of the network that does all the routing, on Outposts servers, and we can distribute those all over the place. So, we're keeping on the innovation. We're keeping on the expansion. And we've been getting very good customer feedback- >> So all steam ahead, full steam ahead? >> Full steam ahead plus 10%. (John laughs) >> All right, guys. Thank you so much, George. Really appreciate it. We're seeing the cloud expand. The definition is growing, kind of like the universe, John. Dave Vellante for John John Furrier. You're watching "theCube" at AWS re:Invent, the leader in high tech coverage globally. We'll be right back.

>>Good morning. It's the cube live from Las Vegas. This is day four of our coverage at AWS reinvent 2021. I'm Lisa Martin with Dave Nicholson. We have had since Monday two live sets two remote studios over 100 guests on the program. This is a 10th annual reinvent. We're talking about the next decade of cloud innovation and we're pleased to welcome Ashley Kramer, the chief product officer and chief marketing officer of Sisense to the program. Welcome Ashley, thanks for having me today. So you own marketing and product. Tell me a little bit about your role. Obviously that's done. >>It's a big role. It has a big role, but I think as the analytics ecosystem has evolved, it makes sense to bring the product you're building the platform you're building and the messaging that you're taking to market together in one. And so I've been in size since almost two years, and I am responsible for both the messaging and the building of the product. >>Awesome. Talk to me a little bit about the next generation of business intelligence. Define Gen-Z one, two and where we are with three. >>Yeah. So when we think about the generations of analytics and we think about how the world is evolved, we're here clearly at a cloud conference, data apps, and the way people work has evolved over time. And I think analytics hasn't quite kept up and I'll explain what I mean about that. The first generation of analytics was really about, you know, that we're talking by the way, late nineties, early two thousands, big on-premise servers of data, things that would make people here sort of cringe, right? And the way to extract value was to put an analytics server right next to it, go wait in line, ask her it, Hey, I need a report. And then wait a few weeks. That report gets delivered. It's the wrong data. It's now stale. You've got to go get back in line, enter gen two, which by the way, I was a part of in my career at Tableau. >>And what we said was let's put data at everybody's fingertips. Let's allow people via desktop tool to drag and drop and build the perfect, beautiful dashboard. And then we can deploy it to everybody and we will break down that barrier to it. And that was successful. But the one thing that we didn't understand was not, everybody's an analyst, not everybody's data literate and dashboards could be very, very intimidating to the everyday worker. And so now we're on the cusp of what we call gen three and sysynced is well-positioned to really nail this market, which is make data invisible, make analytics invisible, and bring it to where people are. And that's what we consider gen three. And I of course can talk about that for hours. So I'd love to talk more about it. >>So are the lines blurred between what people think of as artificial intelligence and BI, because you're talking about, um, you know, making this invisible or transparent, you know, frictionless access, um, are you talking recommendations or just a presentation of raw information? How are those two topics, interleaved >>Talking both. And so what's, what's really beautiful about this is the dashboard doesn't have to go away, but you have to break it apart and you have to make it less intimidating, more approachable, more understandable, which is where AI comes in natural language generation, natural language querying maybe for some people, maybe for a doctor, they want to see the data presented in plain text, plain English. Great. Let them do that. And so AI is a big, big piece of this gen three. When we think about where BI and analytics is evolving to. So >>Like it, from a customization perspective, you're going to be able to allow people in healthcare, finance, marketing, sales, operations products, be able to have data at their fingertips when they need it. Because one of the things that we learned in the pandemic is that access to real-time data is no longer a nice to have it's required. But to your point, if it's intimidating or if it's inaccessible, or if it's too complicated, it's not useful. >>That's right. And what we also learned during the pandemic is people are busy and they don't have time to change what they're doing. They don't have time to leave their everyday workflow and process to go look for something. They don't have time to look for an unnatural experience and try to interpret what it says. So customization is a huge piece of this, make it look and feel the way that a healthcare worker needs it to look and feel, make it look and feel the way that, you know, a construction worker makes it as part of their everyday job. And that's a core piece of gen three as well. >>What are some of the things that you guys are doing with AWS? Obviously, AWS, very, very customer focused. They always talk about working backwards from the customer, really this customer obsession. What are some of the things that you guys are working on together that your joint customers will benefit from? >>Fun fact, I was Amazonian as part of my career. So I grew up with Amazon in the early days of AWS. And we are very close partners with them from two really big perspectives. The first is the data's moving there, all of the data, particularly things like red shift. And that is a perfect place for size sense to sit right on top of that data, query it live, bring that and extract it to people in the way that they need it to consume. It really make data-driven decisions. The second piece is, um, and we saw a great keynote yesterday by Swami, which is the AI piece of the story, the comprehend, the Lexio, you know, really bringing to people, the data and the information and the way they need, and that all plugs into the size sense experience. And we can be that visual front end layer on top of all of those services. >>So where you sit because of your purview, looking at product marketing, and then let's, let's make, let's make the third point in the triangle, the customer always what, from your perspective, because you're thinking in terms of product customer requirements, and then you're thinking about how do you get the message across to make sure people understand what you're doing? What does a delighted customer sound like to you? What makes you smile? When someone says, Hey, Ashley, we have this customer who absolutely loves us. And these are the things they love about us. What does, what does that sound like? >>Really a very, very simple thing to answer because through my career too often, and I've read products at all of the companies I've worked for, you sell these big deals and you help them be successful with one use case. And you come back a year later in three people in the organization are actually using that solution to make data-driven decisions. So my perfect customer is, you know, we take them by the hand, we help them deploy that we come back a year later and the entire organization, all of their customers are using the solution because we've made it more approachable, more personalized and less intimidating. >>So what's the opposite of shelf ware. That's what you just described >>The opposite of shelfware and that breaks down every stat you see out there, there's a really widely known one that, um, less than 30% of organizations are actually successful with their analytics solutions. And my theory, my thesis and the research that we've done is that's exactly why it's too intimidating. It's too clunky and it's too disjointed. >>So talk to me, I, one of the things I think is the best validation of brand can get is the voice of the customer. I agree with you that it's, it's exciting when you, cause there's, there's so many, there's so many tools and you just mentioned the stat, um, in terms of adoption, but share with us a customer example that you think really articulates the value of what you're talking about. That gen three BI customizable, personable, what customer comes to mind are customers. You have. >>So one of my favorites is a company called outreach and what outreach outreach caters to is sales. It's, you know, early sales, sales enablement, helping people understand which customers should I go target. And should I go sell to, these are not analysts using the platform. And when outreach came to us, they said, we want data and analytics to drive our experience for all of our customers. But these are young salespeople. They can't just be looking at dashboards. And so what we've done with them is we were actually the AI engine that drives the experience. And as that BDR, ADR SDR gets in there, they're actually using analytics to figure out who to call what account is hot, what to do next, and right. They're actioning right in the experience. And they have no clue that they're will using data. And that's okay. And they're optimized. They're more efficient at their job because science is powering that experience. >>So they could be in Salesforce and accessing this, like under the covers, not even knowing it, they have no idea >>Exactly >>What they're empowered with BI AI to be able to make decisions. >>And they're becoming better at their jobs because they're using data and they're not learning a new skill set because they don't have time. There's no time. >>That's a great point. One of the other points that we've heard a lot, the last three days is every company has to become a data company. One thing to say it whole other can of worms, right? To actually enable it. Because to your point earlier, you have access to data it's confusing or it's stale. There's a competitor right here. Ready to take over. Talk to me about how your customer conversations have changed, especially in the last 22 months about how do we become data really? Data-driven, >>That's, that's interesting because if you would've asked me two, three years ago, I would have given you this big pitch on, well, we need to go in and help them build this culture of data and analytics, right? We're going to go in and help them. That has changed. What we need to do now is accept that building. That whole culture is too hard to do. It requires people to go beyond their job and really learn a new skill set. So what we do is we make every company, a data company by not necessarily making them really realize that they're using analytics and data. We're making it personalized. We're removing the nuances that come with building the state of literacy culture. So yes, you still need to build the culture around it and have the support, but you need it to be less intimidating and you need it to just be part of the everyday workflow, the everyday process, the everyday experience, regardless of job title. There's another interesting stat that there's over 1 billion knowledge workers out there that are underserved. That's the barrier we need to break down. Next analysts are happy. Data scientists are happy. They have what they need. How do we get what they're doing to those 1 billion plus underserved knowledge workers. >>So when you're in customer conversations and they're like, Ashley, help us figure this out. >>You say, we go in and we show, you know, we, we figure out what their business case is. And they very often say, okay, let's start with a big, huge dashboard. Step them back and say, what are you really trying to solve? Okay. You want that doctor to be more efficient? You want to triage more properly, maybe right there within your system, within your medical system. We're just going to pop, you know, we're going to pull data out of red shift and we're just going to pop some insights there. Some recommendations, as you mentioned earlier, some plain text, we'll give you a search experience so you can search, you know, what beds are open and it will bring it back to you the way that you understand how to work, you don't have to change. >>And that's critical because one of the things that we talk about all the time is change management, cultural change. It's really hard to do, especially given the dynamics of the environment that we're in. People are still scattered, working from anywhere. That's going to persist for a while. We need to meet them where they are >>Absolutely a hundred percent nailed it. And I'm going to steal that in my marketing material. Thank you. I'm a marketer trademarks. Um, but absolutely meet them where they are. And you know, everybody wants to evolve. Everybody wants to upscale and you can help them, but don't expect it to happen overnight. And don't expect they're going to take it on as a second job because their core job function is the most critical. >>It's interesting from a marketer's perspective. Um, it's always great to have people running around wearing size sense, hoodies on the customer site what's even better is having them using the product. And maybe they don't even know as long as key stakeholders in the organization knows so that you can drive, you know, drive into the market. But is there anything disheartening about sort of being toiling in obscurity at times? >>It is the hardest part of the CMO hat that I wear is you both are very likely using size sense in something that you're doing and you have no idea. And that is a brand's nightmare. So yes, checking my pockets. In fact, we are giving away Fanny packs. And as soon as I'm done, I will be over here with two Fanny packs for you. Apparently that's the new thing. That's what the kids are doing. Um, but it is very hard. It's um, we have to do more because lots of people are using size sense and actually lots of people at this conference right now, a lot of these vendors have size sense embedded, and they don't necessarily know they're using it. It's a double-edged sword though, >>Because you're saying, you know, the whole point is making analytics invisible. So, but it is, but I'll take the Fanny pack. >>I'll be out. Don't worry about that. Don't you worry? >>So here we are wrapping up 10th annual at reinvent. You were an Amazonian. So you've been to many of these, obviously the first one in two years, there's nothing like the conversations that are going on behind it. There's nothing like an in-person interview to have a really a conversation about the technology. What are some of the things that have you heard at the conference that excite you going into 2022? >>My excitement going in is the focus that everybody's putting just beyond what's next beyond data like the AI, right? The AI perspective of everything, the way that AWS is evolving their data story, lots of serverless spoken by Adam in the first day. And I think there's really, really big things coming. You see the three big clouds competing and making each other better and better. You see vendors like size sense working cross-cloud because everybody has something best in class. And so I am one very excited to be in person and to be shaking hands and hugging friends that I have not seen except over zoom in two years. But I'm really excited for the direction. Particularly AWS is taking the data ecosystem inside sense plans to be a core part of that. >>Awesome. It's exciting. The amount of innovation that has gone on is we think, you know, the next 10 years is we're going to see far more in the next, probably five than we did in the previous 10. Actually. Thank you so much for joining us, talking to us about science. We'll have to, we'll have to think about that. Well, when we get our Fanny pack, so we can talk about science, how we're using it, but awesome. To be able to bring analytics to everyone so that it is invisible, usable, and we can actually extract value from data in real time. Thank you for >>Having me today. Our >>Pleasure for Dave Nicholson. I'm Lisa Martin. You're watching the cube, the global leader in live tech coverage.

(upbeat music) >> Good evening, guys. Welcome back to Las Vegas, theCUBE is here live at AWS re:Invent 2021. I'm Lisa Martin. We have two live sets, two remote sets, over 100 guests on theCUBE talking with AWS, and its massive ecosystem of partners bringing you this hybrid tech event, probably the biggest of the year, and I'm pleased to welcome Stephen Kovac next, the Chief Compliance Officer at Zscaler. Stephen, how's it going? >> Well, it's going well, Lisa. Thank you for asking, enjoying Vegas, loving the conference, unbelievable. >> Isn't it great to be back in person? >> Oh, it's so great, I've seen people. >> Conversations you can't replicate on video conferencing, you just can't. >> Can't, and you see people you haven't seen in two years, and it's like all of a sudden you're best buddies again. It's just wonderful, it's so great to back. >> It is, and AWS in typical fashion has done a great job of getting everybody in here safely. I'm not at all surprised, that's what I expected, but it's been great. And I hope that this can demonstrate to other companies, you can do this safely. >> You can, I think so. I mean, there's a lot of effort going into this, but as usual AWS does it right. So, you expect that. >> They do. Talk to me about the Zscaler-AWS partnership. What's going on? >> Well, it's a great partnership. So AWS and Zscaler have been partners since the beginning of Zscaler. We are the largest security cloud in the world. We're born and bred in the cloud security company. So literally we wrote one application that does global security, everything from firewall to proxy, secure web gateway, to DLP, to all this in one piece of software. So, in the past where people would buy appliances for all these devices and put them in their own data center, we wrote a software that allows us to put that in the cloud, run it on the cloud globally around the world. And our partnership with AWS is, we originally built that on AWS, and today still AWS is our prime partner, especially in the zero trust side of our business. So, great relationship, long-term and great I think for both of us, it's been a very, very... >> Fruitful partnership, synergistic? >> Synergistic, love that, so yes. >> You mentioned zero trust, and we have seen such massive changes to the security and the threat landscape the last 20, 22 months. Talk to me about the recent executive order calling for zero trust, how does Zscaler's partnership with AWS help you enable organizations, fed, SLED, DoD, to be able to actually bring in and apply zero trust? >> Yeah, great question. Five years ago I was tasked to bring Zscaler into the government side of the business. So I was employee one to do that. It was a great honor to do it. And the first thing we did is we partnered with AWS because we needed to get FedRAMP compliant. We knew we were going to go into DoD. So we needed to go to the Impact Level five. And eventually we'll be able to go up level six with AWS. And so it was our partnership started there. And as you've seen in five years with all the change that's happened, that obviously the breaches like SolarWinds, and the people up here talking about them all week with you I'm sure. The executive order came down from the Biden Administration, who I completely salute for being just tremendous leaders in the cybersecurity space. And the executive order, one of the big pieces of the executive order was every agency must produce a plan for zero trust. So our cloud platform that is on AWS is a zero trust platform. It is the first and only zero trust platform to get authorized by the federal government at the FedRAMP level, and now the IL five level. So, together we are literally capturing and taking over the, being the leader in the zero trust space for the federal government. And I'm going to get a sip of water, so forgive me, I've been here all week talking to a lot of people, so forgive me for that. >> That's one thing that we don't have to deal with when we're on Zoom, right, is you don't really have the risk of losing your voice. >> Stephen: There you go. >> But in terms of the executive order, something that you mentioned, SolarWinds, Colonial Pipeline, we only hear about some of the big ones. The fact that ransomware happens one attack every 10, 11 seconds, it's a matter of when we get hit, not if. >> As you know, the story coming up from me, coming up on stage with you today, I just got myself breached just this morning, just individually. So yes, it's going to get all of us. And especially, I think when you look at zero trust and ransomware and how they worked out how zero trust can prevent it, you look at the SLED market, you know, state, local governments, they don't have the dollars to go spend like DHS does, or say, some of the DoD does. So, our partnership with AWS allows us to produce a product that is very cost-effective on a per user basis, consumption model, which is what AWS has been famous for since day one, right, the consumption model, use it when you need it, don't use it when you don't. We built our software the same way. So, at some point in a year, in a school year, we'll ramp up with some schools up to a hundred thousand users in the district, and over the summer we'll ramp down to a thousand, and we just bill them for that. So it's a beautiful relationship that we partner in not just the executive order, but being a partner in SLED, fed in the sense that matches making our business together, match the government's business. And that makes us a true leader and makes us a cost-effective solution. And if you think about it just for a moment, yesterday, I told you I was testifying in front of the Senate. And one of the questions I got asked was, oh, how many security updates do you guys see a year? I said, a year, well, we do over 200,000 a day. 200,000 security updates from potential hackers every single day. And we're doing that over 200 billion transactions a day run on AWS. So it's tremendous partnership, and to be able to work like that, and at that kind of volume, and be able to go up and down with the, and you got AWS able to scope up and down, and us to be able to ride that wave with them. It's been great. >> One of the things that we always talk about when we talk AWS is they're customer focused or customer obsession that, hey, we start backwards, we work backwards from the customer. Same thing, synergistic from a cultural perspective? >> Absolutely, I mean, one of the things I always love about AWS and I've been a customer of AWS for many years, even prior to my Zscaler days, I love the way they approach things, right? If they're not trying to go out and sell it, they're trying to meet with the customer and find out what the customer needs, and then build a solution. We're the same way. I always tell, you know, when you think of our solutions, Zscaler, I always tell my sales teams, I say it takes four sales calls for people to really understand what we do. And AWS, in the beginning of AWS, it was kind of the same thing. In the old days, you know, we all just built data centers and we had all these racks, and all this expense and mesh is what you did. It was unusual back in the day, 10 years ago, and I've been to every single re:Invent. I mean, the first one there was like, you're actually going to put all your stuff in this unknown cloud thing, and it will be available when you need it? So yes, you know, the way that they did it is the same way we do it together today. And we do it together today. We partner on many deals today where we're both, our teams are in there together, selling together, whether it's the DoD, federal agencies, SLED agencies, and commercial, you know, selling it hand-in-hand because it's that same philosophy is we're going to build what a customer needs. We're not going to tell the customer what they need. We're going to hear what they need, and that's the same relationship. So I'm going to get another sip real quick. >> Go for it. One of the things that has been a theme that we've heard the last couple of days is every company needs to be a data company or private sector, public sector, and if they're not, they're probably not going to be around much longer. How do you help customers get their handle around that? Because the security threats are only increasing. I mean, it's ransomware as a service. The fact that these criminals are getting much more brazen, you just had this happen to yourself, but enabling them to become data-driven organizations and use the data, extract the value from it securely, that's hard. >> It is, I mean, if you think back in the day, I mean, companies didn't have chief compliance officers that worked in the space that we do. Their chief compliance officer back in the day was the guy that was writing your HR issues and what OSHA issues, and of course, I still deal with some of that stuff, but my true job is really around the data, right? You know, how do we build our platforms, what decisions we make on our platforms, how we're going to certify them to support that, and I mean, chief data officers, chief security officers, I mean, you go into companies today, even car dealerships today. I mean, I'm picking one, you never thought of them having a security officer, but they do, they have to, they have to. And I mean, basic school districts, I mean, I don't about you, when I was a kid and went to school, they didn't have computers, but when my kid went to school, they did, but they didn't have a security officer. Now today, every single school district has security officers. I mean, I love how you said it, that data-driven, that data thought is there. It has to be, it's a real threat. And the sad thing is of these ransomware attacks, how many don't get reported. >> Oh, right, we're only hearing about a select few. >> The numbers are something like 88% don't get reported. It's that big. So that just tells you, we hear the big ones, right, Colonial Pipeline, things like that. We don't hear about West Texas or Middle Illinois school district that paid five grand because somebody had something on the school. That's how, as you said, this ransomware as a service security, we call it a security as a service, there's SaaS, which is software as a service, we're security software as a service, and AWS is the infrastructure as a service that we run on. And that's how it works well together. >> Do you guys go into accounts together from a go-to-market perspective? >> We, do, we can always do a better job. And my good friend here at AWS, who's probably listening, we can always do better. But yeah, so it is become something that, especially in the government space we do, in federal, DoD, because the certifications are really important, certifications are important everywhere, and we have many, we talked about all the certifications we have in federal, FedRAMP and IL five, and we have a plethora of those certifications in the commercial space. But they mean in a federal space, they're really the ticket. They call them the ENERGY STAR of approval, good housekeeping piece. So, you know, having that, teaming up with AWS who we partner together and because AWS has the same certs, we can sell at the same levels. And we do a really great job of co-selling in that space together. And I think when they look at us and they say, well, you're AWS, they've got their FedRAMP high, IL five, and you're Zscaler, you got your FedRAMP high, IL five. Yes, we can do business with these guys, and that's important. >> So you guys both open doors for each other. >> We do, we do in many cases, yeah. As a matter of fact, re:Invent five years ago, a buddy of mine here opened a big, big account for us, which is today our largest account in federal came from re:Invent, where came up to me and said, hey, my customer wants to, he's looking to do something, they're an agency that has global footprint, and they're like, we want to do something as a security as a service. They don't want to ship boxes all over the place. And we just met the customer for a coffee, and next thing you know, became our, still today, our probably largest customer in federal. >> Wow, well, this is the 10th re:Invent, you said you've been to all of them. >> Stephen: I have been to all of them. I can't lie, but I can't say I did all the virtual ones. I mean, I was logged in. (laughs) >> That's okay, we'll wink on that one. But, one of the things then, we've just got about a minute left here, is in new leadership, Andy Jassy being promoted to the CEO of Amazon, we've got Adam Selipsky, heard lot of announcements and news from Adam yesterday, but some of the things that we've been talking about on theCUBE is the first 15 years of innovation at AWS, that's going to accelerate. Do you see that also, like if you look forward to the next decade, do you see things moving much faster than they did the past decade? >> I don't think they can't. I mean, I shouldn't say they have to. And the change of the guard as you might call it here, is it's always good to have a change of the guard I think. You know, the question is when's Andy going to go to space? I mean, that's the next. (Lisa laughs) I think you have the guys who got AWS to the dance, and now the dance, who's going to become the belle of the ball. And this next generation of leadership coming in is fabulous. I think they've made great decisions, and I think they're going to do really well. And we're behind them, we support it. I got a chance to meet with most of them, love a chance to meet with Andy, I haven't met with him yet. So Andy, I'd love to meet you sometime soon. But I'm very impressed with what they've done. And yes, I think it's going to be, the last 10 years of growth is going to be a year next year. I think literally, you take 10 years be compressed to a year, and then next year it will be compressed to a day. So it's moving that fast. >> Yep, get your neck brace on, prepare for that whiplash. >> Yeah, right? That's what I said to Jeff when Jeff went to space, that's how fast we're about to travel, right? But it's really relative. >> It is, there is no limit. Well, Stephen, thank you for joining me, talking about Zscaler, AWS, what you guys are doing, how you're helping to revolutionize the public sector, fed, SLED, a lot of great stuff there. Security is an ever-evolving topic, and we appreciate all of your insights. >> Well, it was wonderful to be here. Great to see you again. And great to be back with all our friends at re:Invent. >> All of our friends, exactly. >> Stephen: Thank you so much for the time today. >> My pleasure. For Stephen Kovac, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (pleasant music)

(upbeat music) >> Hey, welcome back to Las Vegas. theCUBE is live at AWS re:Invent 2021. I'm Lisa Martin. We have two live sets, theCUBE. We are running one of the largest hybrid tech events, most important events of the year with AWS and its massive ecosystem of partners like as I said. Two live sets, two remote sets. Over a hundred guests on the program talking about the next generation of cloud innovation. I'm pleased to welcome a first timer to theCUBE. Seth Rao, the CEO of FirstEigen joins me. Seth, nice to have you on the program. >> Thank you nice to be here. >> Talk to me about FirstEigen. Also explain to me the name. >> So FirstEigen is a startup company based out of Chicago. The name Eigen is a German word. It's a mathematical term. It comes from eigenvectors and eigenvalues which is used and what it's called is principal component analysis, which is used to detect anomalies, which is related to what we do. So we look for errors in data and hence our name FirstEigen. >> Got it. That's excellent. So talk to me. One of the things that has been a resounding theme of this year's re:Invent is that especially in today's age, every company needs to be a data company. >> Yeah. >> It's all one thing to say it's as a whole other thing to be able to put that into practice with reliable data, with trustworthy data. Talk to me about some of the challenges that you help customers solve 'cause some of the theme about not just being a data company but if you're not a data company you're probably not going to be around much longer. >> Yeah, absolutely .So what we have seen across the board across all verticals, the customers we work with is data governance teams and data management teams are constantly firefighting to find errors in data and fix it. So what we have done is we have created the software DataBuck that autonomously looks at every data set and it will discover errors that are hidden to the human eye. They're hard to find out, hard to detect. Our machine learning algorithms figure out those errors before those errors impact the business. In the usual way, things are sorted out, things are done. It's very laborious, time-consuming and expensive. You have taken a process that takes man-years or even man-months and compressed it to a few hours. >> So dramatic time-savings there. >> Absolutely. >> So six years ago when you guys were founded, you realize this gap in the market, thought it's taking way too long. We don't have this amount of time. Gosh, can you imagine if you guys weren't around the last 22 months when certainly time was of the essence? >> Absolutely. Yeah. Six years ago when we founded the company, my co-founder who's also the CTO. He has extensive experience in validating data and data quality. And my own background and my own experiences in AI and ML. And what we saw was that people are spending an enormous amount of time and yet errors were getting down through to the business side. And at that point it comes back and people are still firefighting. So it was a waste of time, waste of money, waste of effort. >> Right. But also there's the potential for brand damage, brand reputation. Whatever products and services you're producing, if your employees don't have the right data, if there's errors there of what's going out to the consumers is wrong then you've got a big problem. >> Absolutely. Interesting you should mention that because over the summer there was a Danish bank, a very big name Danish bank that had to send apology letters to its customers because they overcharged them on the mortgage because the data in the backend had some errors in it and didn't realize it was inadvertent. But somebody ultimately caught it and did the right thing. Absolutely correct. If the data is incorrect and then you're doing analytics or you're doing reporting or you're sending people a bill that they need to pay it better be very accurate. Otherwise it's a serious brand damage. It has real implications and it has a whole bunch of other issues as well. >> It does and those things can snowball very quickly. >> Yeah. >> So talk to me about one of the things that we've seen in the recent months and years is this explosion of data. And then when the pandemic struck we had this scattering of people and data sources or so much data. The edge is persistent. We've got this work from anywhere environment. What are some of the risks for organizations? They come to you and saying help us ensure that our data is trustworthy. I mean that the trust is key but how do you help organizations that are in somewhat a flux figure out how to solve that problem? >> Yeah. So you're absolutely correct. There is an explosion of data, number one. And along with that, there is also an explosion of analytical tools to mine that data. So as a consequence, there is a big growth. It's exponential growth of microservices, how people are consuming that data. Now in the old world when there were a few consumers of data, it was a lot easier to validate the data. You had few people who are the gatekeepers or the data stewards. But with an explosion of data consumers within a company, you have to take a completely different approach. You cannot now have people manually looking and creating rules to validate data. So there has to be a change in the process. You start validating the data. As soon as the data comes into your system, you start validating if the data is reliable at point zero. >> Okay. >> And then it goes downstream. And every stage the data hops that is a chance that data can get corrupted. And these are called systems risks. Because there are multiple systems and data comes from multiple systems onto the cloud, errors creep in. So you validate the data from the beginning all the way to the end and the kinds of checks you do also increase in complexity as the data is going downstream. You don't want to boil the ocean upfront. You want to do the essential checks. Is my water drinkable at this point, right? I'm not trying to cook as soon as it comes out of the tap. Is it drinkable? - Right. >> Good enough quality. If not then we go back to the source and say, guys, send me better quality data. So sequence, the right process and check every step along the way. >> How much of a cultural shift is FirstEigen helping to facilitate within organizations that now don't... There isn't time to, like we talked about if an error gets in, there's so many downstream effects that can happen, but how do you help organizations shift their mindset? 'Cause that's hard thing to change. >> Fantastic point. In fact, what we see is the mindset change is the biggest wall for companies to have good data. People have been living in the old world where there is a team that is a group, much downstream that is responsible for accurate data. But the volume of data, the complexity of data has gone up so much that that team cannot handle it anymore. It's just beyond their scope. It's not fair for us to expect them to save the world. So the mindshift has to come from an organization leadership that says guys, the data engineers who are upfront who are getting the data into the organization, who are taking care of the data assets have to start thinking of trustable data. Because if they stopped doing it, everything downstream becomes easy. Otherwise it's much, much more complex for these guys. And that's what we do. Our tool provides autonomous solution to monitor the data. It comes out with a data trust score with zero human input. Our software will be able to validate the data and give an objective trust score. Right now it's a popularity contest. People are saying they vote. Yeah, I think I like this. I like this and I like that. That's okay. Maybe it's acceptable. But the reason they do it is because there is no way to objectively say the data is trustable. If there is a small error somewhere, it's a needle in the haystack. It's hard to find out, but we can. With machine learning algorithms our software can detect the errors, the minutest errors, and to give an objective score from zero to a hundred, trust or no trust. So along with a mindset, now they have the tool to implement that mindset and we can make it happen. >> Talk to me about some of the things that you've seen from a data governance perspective, as we've seen, the explosion, the edge, people working from anywhere. This hybrid environment that we're going to be in for quite some time. >> Yeah. >> From a data governance perspective and Dave Vellante did his residency. We're seeing so many more things pop up, you know different regulations. How do you help facilitate data governance for organizations as the data volume is just going to continue to proliferate? >> Absolutely correct. So data governance. So we are a key component of data governance and data quality and data trustworthiness, reliability is a key component of it. And one of the central, one of the central pillars of data governance is the data catalog. Just like a catalog in the library. It's cataloging every data asset. But right now the catalogs, which are the mainstay are not as good as they can be. A key information that is missing is I know where my data is what I don't know is how good is my data? How usable is it? If I'm using it for an accounts receivable or an accounts payable, for example, the data better be very, very accurate. So what our software will do is it'll help data governance by linking with any data governance tool and giving an important component which is data quality, reliability, trustability score, which is objective to every data asset. So imagine I open the catalog. I see where my book is in the library. I also know if there are pages missing in the book is the book readable? So it's not good enough to know that I have a book somewhere but it's how good is it? >> Right >> So DataBuck will make that happen. >> So when customers come to you, how do you help them start? 'Cause obviously the data, the volume it's intimidating. >> Yeah. >> Where do they start? >> Great. This is interestingly enough a challenge that every customer has. >> Right. >> Everybody is ambitious enough to say, no, I want to make the change. But the previous point was, if you want to do such a big change, it's an organizational change management problem. So the way we recommend customers is start with the small problem. Get some early victories. And this software is very easy. Just bring it in, automate a small part. You have your sales data or transactional data, or operational data. Take a small portion of it, automate it. Get reliable data, get good analytics, get the results and start expanding to other places. Trying to do everything at one time, it's just too much inertia, organizations don't move. You don't get anywhere. Data initiatives will fail. >> Right. So you're helping customers identify where are those quick wins? >> Yes. And where are the landmines that we need to be able to find out where they are so we can navigate around them? >> Yeah. We have enough expedience over 20 years of working with different customers. And I know if something can go wrong we know where it'll go wrong and we can help them steer them away from the landmines and take them to areas where they'll get quick wins. 'Cause we want the customer to win. We want them to go back and say, look, because of this, we were able to do better analytics. We are able to do better reporting and so on and so forth. We can help them navigate this area. >> Do you have a favorite example, customer example that you think really articulates that value there, that we're helping customers. We can't boil the ocean like you said. It doesn't make any sense, but customer that you helped with small quick wins that really just opened up the opportunity to unlock the value of trustable data. >> Absolutely. So we're working with a fortune 50 company in the US and it's a manufacturing company. Their CFO is a little in a concern whether the data that she's reporting to the Wall Street is acceptable, does it have any errors? And ultimately she signing off on it. So she had a large team in the technology side that was supporting her and they were doing their best. But in spite of that, she's a very sharp woman. She was able to look and find errors and saying, "Something does not look right here guys. Go back and check". Then it goes back to the IT team and they go, "Oh yeah, actually, there was an error". Some errors had slipped through. So they brought us in and we were able to automate the process, What they could do. They could do a few checks within that audit window. We were able to do an enormous number of checks more. More detailed, more accurate. And we were able to reduce the number of errors that were slipping through by over 98%. >> Big number. >> So, absolutely. Really fast. Really good. Now that this has gone through they feel a lot more comfortable than the question is, okay. In addition to financial reporting, can I use it to iron out my supply chain data? 'Cause they have thousands of vendors. They have hundreds of distributors. They have products all over the globe. Now they want to validate all the data because even if your data is off in a one or 2%, if you're a hundred plus billion dollar company, it has an enormous impact on your balance sheet and your income statement. >> Absolutely. Yeah. >> So we are slowly expanding as soon as they allow us. They like us now they're taking it to other areas from beyond finance. >> Well it sounds like you have not only great technology, Seth but a great plan for helping customers with those quick wins and then learning and expanding within and really developing that trusted relationship between FirstEigen and your customers. Thank you so much for joining me on the program today. Introducing the company, what you guys are doing really cool stuff. Appreciate your time. >> Thank you very much. >> All right. >> Pleasure to be here. >> For Seth Rao, I'm Lisa Martin. You're watching theCUBE. The global leader in live tech coverage. (upbeat music)

(bright music) >> Welcome back to Las Vegas. It's theCUBE live at AWS re:Invent 2021. Lisa Martin here with Dave Vellante. We have two live sets, continuous CUBE coverage. That's what we mean by that. Two remote sets, over a hundred guests on the program at re:Invent 21, lots of content. We are running one of the largest hybrid tech events with AWS and its enormous ecosystem of partners talking about the next decade of cloud innovation. Dave and I are pleased to welcome John Purcell, the Chief Product Officer of DoiT international to the program. John, how's it going? >> It's going well. It's nice to meet you both. Thanks for having me. >> Likewise, nice to meet you as well. Talk to us about DoiT. Who are you guys, what do you do, and then we'll talk about your relationship with AWS. >> Sure, Lisa. Yeah, so we're a global technology company and our mission is pretty simple. Companies are embracing the public cloud at an incredible rate as we all know. That's why we're here. And we simply set out to help them do that well. Help them be successful. Drive the objectives that they've got in terms of why they originally adopted the cloud in the first place. We have a pretty unique value proposition, I would say. We do three things with companies like this. First is we resell you the public cloud. So you will build through us. And as a follow-up to that, we do three things. We provide an intelligent technology portfolio that's available to you to use. We provide an advanced set of advisory and consulting services available to you. And we provide a 24/7 unlimited technical support, both for our technology and for your cloud. And all of that is available to you at no additional costs as a client of DoiT. So it's a pretty unique value proposition. >> Got it, okay. And so tell me about some of the things that you've noticed in the last 22 months with the pandemic. We've seen this massive acceleration of digital transformation, cloud adoption. Obviously, every company now becoming a data company, or if they're not, they're not going to be around much longer. Have you seen any industries in particular that are really come to do it? It's like guys help us out. We've got to move fast. >> Sure. So, there are hundreds of thousands, maybe millions depends on what can you believe or when you read it, but these are all companies who are adopting the cloud. They've bought into the promise of the cloud. And this has been going on now for a few years, perhaps a decade. Certainly, AWS has been doing this for 15 years now. And we suddenly saw certainly during the pandemic an acceleration of that. But we particularly focused on companies who were already in the cloud. They're poised for growth, they're technology savvy in many cases, in almost all cases. And these are specifically who we target. They don't need remedial level assistance. They're technical experts, so to speak. And so we can provide an additional level of help for their most complex, but still essential problems. And so they're the tier of companies we mostly focus on. >> And you said earlier you do the billing. You have basically white labeling the cloud. >> That is our primary business, Dave. Yes, we will resell you. So you consume all of the same services, all of the same technology, but you can then take benefit from in the public cloud. You simply transact through DoiT. >> Okay. So I'm trying to square the circle between you have highly technical people that obviously could figure out cloud pricing on their own, but yet at the same time, you're that layer between which simplifies things. Is that because the highly complex teams want to or technical teams want to spend time doing other stuff, or? >> That's primary, I think that's a good insight, Dave. I think a lot of companies, whether you're born in the cloud or migrating to the cloud, you're doing it for a set of reasons that I think are well-established at this point. It's agility, it's acceleration, it's competitive resistance. I need to be able to take advantage of the newest and most emerging technologies, but something happens on your way to the cloud. There's a set of management responsibilities that in many cases have been around as long as IT has been around, but don't disappear just because you've chosen to build your business in the cloud. And so when companies look to DoiT, what we can provide for them is the level of assistance to alleviate some of that management burden. And again, these are not companies who are looking at very basic, simple entry level questions, like which cloud should I choose? These are companies who in many cases have chosen a cloud. They're operating. They've built infrastructure. They have a cloud estate and they're poised for that growth. So in many cases it's, am I architected for scale? Am I secure across the entire surface area? Have I chosen the right technologies for the next phase of the business evolution? >> You're an accelerant. >> We're an accelerant. >> And then large, medium, small, yes. All of the above. >> All of the above Dave, I would say. If you're a company that's in the cloud, you are technically savvy and you're poised and ready for growth. We're interested to talk to you. We can provide support. >> I want to get your point of view on something, John. So initially the cloud, when Amazon turned the cloud into an API and allowed small companies to have data center infrastructure, the same as big companies compete. And then the big companies caught on and was undergoing this massive IT transformation. And if you saw the Goldman deal this morning. Goldman Sachs is basically creating a Uber super cloud on top of AWS, allowing their hedge funds access to their data, their tooling, essentially their SaaS that they've built. So the big guys are like, almost have an advantage now because that's a highly technical thing to do. And I wonder if the little guys in this next transformation to get left out, can you help? Is that something you do? What do you think about that balance of power if you will, between small and big? >> Well, I think it's really about what your success objectives are. I mean, Goldman Sachs is a global banking, global financial services company. They have a different set of expectations to satisfy their global demand, their clients, their companies, their portfolios. The need is simply one of scale, I would say. What are the real value propositions that you're trying to provide to your customer base? And whether you're a 10 person startup with a modest level of infrastructure and spend in the cloud, or you're Goldman Sachs. Interestingly, a lot of the problems are consistent. It's similar between the two. The cloud is dynamic. By its very nature, it's an elastic thing. It scales up, it scales down. It ebbs and it flows. So the dynamic and constant or continuous rate of change, poses similar sets of problems for Goldman, just as it would for any of the startups you see. >> And the problem is getting it right? >> Getting it right, maintaining an awareness of what's going on, making sure that you're spending the right amount of money on the right services to what we call rate optimized. And making sure that you're secure, that you have visibility into what's changing the beauty of the cloud, the promise of the cloud, is that we can have compute memory and storage whenever we want it, drop of a hat. The flip side of that is anyone can get it whenever they want within your organization. And so maintaining some control and governance over that process is the same for large and small. >> So then, where are you having customer conversations? You talked about the maturation level of the customers that you are working with large and small, but where are your conversations? Are they within the IT stack? Are they higher level? Knowing that you got organizations that already obviously understand the value of the cloud, but need to optimize it, need to grow, need to scale. Has that conversation elevated, especially in the last 22 months? >> I think traditionally, movements to the cloud and the kinds of problems we end up focusing on are very engineering, DevOps, who cares about scale, who cares about choosing the right technology, solving the right technology problems. But increasingly, when you fuse technology and the scale of technology with, how do you pay for it, how do you budget for it, how do you govern it, and how do you make sure that the rollout into the cloud is done proportional to your business expectations, indexed to things like business growth. That's where you see that overlap between let's say finance and engineering and creating a common language for both of those constituents to use when we talk about we need to budget for our spend. That's really difficult to do in the cloud. It's not as simple as just look up a price sheet and away we go. It's so dynamic. It creates a really interesting problem and a very hard problem. >> You guys have done a nine figure raise. So obviously, you're more than a consultancy. You've got a tech stack of your own. Maybe you could talk about your portfolio. >> Sure, so we are a technology company and we invest in a couple of keys. I would say three key areas in order to help solve the problems we're talking about. Number one is what we call analytics that matter. One of the hardest things to keep track of because of the dynamic nature of cloud infrastructure is what's coming and going and what is it costing, what is the true cost to the business, and how do we put some governance around that in the form of budgets and so forth. But making sense of that from one company to the next, they're very inconsistent. Your business looks different to my business, looks different to the next person's business. So creating a set of insights that are relevant specifically to your business is a tricky proposition. So that's why we call it analytics that matter to you. So that's a big area of investment in the tech portfolio. The second area we invest in is what we call simply cost savings. So once you know what your spend base looks like. Once you know what's going where, the trick then is to find ways to optimize that. It's not always about reducing costs. This is sort of a common, you hear this a lot in the industry. How do I reduce my cost? It's about optimizing it to the right level. So that increase in costs might be fine if your business is growing. So our goal is to provide smart software that helps you find the right rate for your unit of consumption and then use software to automatically apply that. And then the third area, if I could just finish on that note is what we call proactive governance. And that's simply most basic form of financial governance is a budget. How can we set a budget and then look for situations where we might be in jeopardy of breaching that or exceeding what we've set as our governance controls. >> So where in those three areas do you use machine intelligence? All three? I mean, maybe you could talk about how you're injecting AI? >> Yeah, that's great. So we use it in as many places as we think is relevant. So certainly when you're looking at large datasets, for example, billing and usage data, leveraging advanced algorithms, like various machine learning techniques to help you look for patterns, to help you derive, look at project forward looking expectations based on what you've seen up to date is a really interesting machine learning use case. And so when we're looking at forecasts, this is your spend month-to-date. This is where we expect you to finish the month. Very common sort of intuitive use case. When you set a budget, we can predict for you pretty accurately when you will hit that limit or the threshold on the way to that limit. And then one of the final ways we leverage machine learning today is what we call anomaly detection. So we talked about it, a lot of things changing, not always intentional, not always for the betterment of the business. So if something happens in your cloud estate, for example, mistake or misconfiguration, and it creates a spike in usage or it creates what we might say as anomaly, unexpected behavior, we can catch that. We can look at the patterns, catch that, and then take action. So those are the three most common areas we use machine learning today. >> Can you give us an example of a customer that you think that you working with, that really articulates the value of what DoiT is enabling and what you're delivering customers? >> Well, it's like picking your favorite child. (Lisa laughs) We work with over 1500 customers today, around the world. Various sizes as we discussed earlier. The range of challenges and problems they bring to us is wide and varied. And that's one of the big challenges that we're working hard to try to maintain a pace, to keep pace with. So we're working very hard, you can imagine when a company is choosing a technology partner, like DoiT, you've got to earn that trust. You've got to earn their trust because you're taking action sometimes on their behalf using software. So we've got to work hard to earn it. We've got to demonstrate it and now we've got to keep it. So especially in the world of SaaS and cloud, you're always re-earning and re-upping that trust. So I'd rather not pick a favorite customer. They're all favorites of mine. >> I should have ask early on. What is cloud to you? Is it purely public cloud or is it hybrid? >> It's public cloud primary. That's where we focus. So if you're a growing company, poised for growth, using one or more public clouds, that's our sweet spot. >> And what's your roadmap look like? Give us a little perspective on where you're headed. >> Yeah, so our roadmap. So we have, I would say a pretty rich and rather daunting, I would say, strategy that we need to execute over the next 12 to 18 months. And it's driven primarily, Dave, by the problems that we talked about, that our customers bring to us. That's the beauty of working in a company that's both a technology, a deep technology company, and has a strong advisory and consultancy angle. The problems we hear about are real operational, real world problems. They're not here's a problem we think you should have and you don't know you have, and here's a solution to that. You may not have known existed. These are problems, mostly reacting to things we deal with on a daily basis. So whether it's analytics and insights, as we talked about whether it's cost savings and making sure that we can apply rate optimization across compute memory storage network. You name it, anywhere that you can derive. For example, discounts or savings in the cloud. We need to be able to automatically apply those. And then finally, the proactive governance is a big area of focus for us over the course of 22. And so we'll continue to sort of invest broadly and deeply across each of those areas. >> Last question for you, as we wrap up here. One of the things that we talk about with AWS all the time is their, Hey, we work backwards from the customer first, that sort of customer obsession. It sounds like you were talking about from an advisory perspective that the customers that do it works with are really influential on that roadmap that you just talked about, on the direction that you guys are taking the company. >> I would say, one of the things that you'll find as when you talk to product people and companies, and you probably know yourself is that you always want to have more customer interaction. You can never have enough because there's nothing worse than investing, building, shipping and it's not used. So for us, I'm delighted. I mean, this is one of the first companies I've worked for that has a really rich and dynamic and very deeply qualified set of customer interaction and feedback. So, my colleagues will appreciate when I say it's rather easy to pick the things that we know are going to be truly valuable and truly used. So it is, it was mentioned. Adam mentioned it in the AWS keynote yesterday about from customer backwards. We're very much the same and we have a strong set of customers that are vocal and we're delighted to have them. >> Excellent. John, thank you so much for joining Dave and me on the program, talking about what you guys are doing and how you're helping businesses really accelerate in every industry. We appreciate your insights and your time. >> It's a pleasure to meet you both. Thank you. >> Likewise for Dave Vellante. I'm Lisa Martin. You're watching theCUBE at AWS re:Invent. theCUBE, the global leader in live tech coverage. (bright music)

>>Welcome back to the cubes. Continuing coverage of AWS reinvent 2021 live from Las Vegas. I'm Lisa Martin. We have to set two live sets here with the cube two remote sets over 100 guests on the program for three and a half days talking about the next decade and cloud innovation. And I have two alumni back with me. Please. Welcome back, Mandy Dolly, while the CMO of Boomi and ed. Makowski the head of product at Boomi guys. It's so great to see you. Great to see you, Lisa, thank you in person zoom. Incredible. So in the time, since it's been, since I've seen you, booty is a verb. You, I can see your cheeks bursting. Yeah. Just >>Boom, yet go, boom. It go. Boom. Yet, >>Talk to me about what, what that means, because this is something that you discovered through customers during the pandemic. >>Absolutely. And really it's a Testament to the platform that's been built and the experience of 18,000 customers, a hundred thousand community members, anytime there's disparate data. And it needs to be connected in a way that's secure, reliable performance. And it just works that confidence and trust our customers are telling us that they just Boomi it. And so we figured it was a rally cry. And as a marketing team, it was handed to us. We didn't have to push a Boulder up hill. Our customers are, are just booming it. And so our rally cry to the market is take advantage of the experience of those that have come before you and go build what you need to. It works, >>Period. It works well as the chief marketing officer, there's probably nothing better, nothing better than the validating voice of the customer, right? That's the most honest that you're going to get, but having a customer create the verb for you, there's going to be nothing that prepares you for that. Nothing like it, but also how great does that make it when you're having conversations with prospective customers or even partners that there's that confidence and that trust that your 18,000 plus now customer's house right in >>Lummi right. And adding what? Eight a day. Yeah. Every day we're adding eight new customers. >>Thank you customers a day. The Boomi versus what? A hundred thousand strong now. Yes. >>In two years we built that. Is that right? Yes. >>Wow. Oh my goodness. During the >>Pandemic, the momentum is incredible. Yeah. It's >>Incredible. >>Then you're on your growth from a usage perspective. So yeah, we're skyrocketing >>Use the most need like, uh, you know, neck braces from whiplash going so fast. >>Oh, we're ready. >>Good. I know, I know you are. So talk to me about, you know, we've seen such change in the last 22 months, massive acceleration to the cloud digital transformation. We're now seeing every company has to be a data company to survive and actually to be competitive, to be a competitor. But one of the things that used to be okay back in the day was, you know, these, uh, experiences that weren't integrated, like when you went to well, like when I was back in college and I would go in and you would pay for this class and that cause everything was disconnected and we didn't know what we didn't know. Now the integrated experience is table stakes for any organization. And talk to me about when you're talking with customers, where are they like across industries and going, we don't have a choice. We've got to be able to connect these experiences for our customers, for our employees and to be a comparator. >>Okay. Yeah. I mean, it used to be about for us application data integration, that sort of thing. That's where we were born. But particularly through the pandemic, it's become integrated experiences and automation. It's not just about moving data between systems, that sort of thing. It's about connecting with your end users, your employees, your customers, et cetera, like you were saying, and automating and using intelligence to continue automating those things faster. Because if, if you're not moving faster in today's world, you're, you're in peril. So, >>And that was one of the themes that we were actually talking about this morning during our kickoff that you're hearing is every company is a data company. And if they're not, they're not going to be around much longer many. Talk to me when you're talking with customers who have to really reckon with that and go, how do we connect these experiences? Because if we can't do that, then we're not going to be around. >>Yeah. The answer lies in the problems, right? There are real-world problems that need to be solved. We have a customer just north of here, a, a university. And, um, as they were bringing students back to campus, right, you're trying to deliver a connected campus experience. Well, how do you handle contact tracing, right. For COVID-19 that's a real modern day problem. Right? And so there you're able to now connect disparate data sources to go deliver on a way, an automated way to be able to handle that and provide safety to your students. Table-stakes oh, it is right. Digital identity management again in a university set setting critical. Right? So these things are now a part of our fabric of the way we live. The consumerization of tech has hit B2B. It's merging. Yeah. >>And it's good. There's definitely silver linings that have come out of the last 22 months. And I'm sure there will be a few more as we go through Omicron and whatever Greek letter is next in the alphabet, but don't want to hear we are at reinvent so much. There's always so much news at reinvent. Here we are. First 10th, 10th reinvent. You can't believe 10th reinvent. AWS is 15 years old brand new leader. And of course, yesterday ad starts the flood of announcements yesterday, today. Talk to me about what it's like to be part of that powerful AWS ecosystem from a partner perspective and how, how influential is Boomi and its customers and the Boomi verse in the direction that AWS goes in because there's so customer obsessed like you guys are >>Well, it was really exciting for us because we're a customer and a partner of AWS, right? We, we run our infrastructure on AWS. So we get to take advantage of all the new announcements that they make and all the cool stuff they bring to the table. So we're really excited for that. But also as all these things come up and customers want to take advantage of them, if they're creating different data, sets, different data silos or opportunity for automation around the business, we're right there for our customers and partners to go take advantage of that and quickly get these things up and running as they get released by AWS. So it's all very exciting. And we look forward to all these different announcements. >>One of the things also that I felt in the last day and a half, since everything really kicked off yesterday was the customer flywheel. AWS always talks about, we work backwards from the customer forwards. And that is a resounding theme that I'm hearing throughout all of the partners that I've talked about. They have a massive ecosystem. Boomi has a massive ecosystem to working with those partners, but also ensuring that, you know, at the end of the day, we're here to help customers resolve problems, problems that are here today, problems that are going to be here tomorrow. How do you help customers deal with Mandy with, with some of the challenges of today, when they say Mandy help us future-proof or integrations what we're doing going forward, what does that mean to Boomi? Yeah, >>I think for us, the way we approach it is you start with Boomi with a connectivity kind of problem, right? We're able to take disparate data silos and be able to connect and be able to create this backbone of connectivity. Once you have that, you can go build these workflows and these user engagement mechanisms to automate these processes and scale, right? So that's 0.1, we have a company called health bridge financial, right? They're a health tech company, financial services company. They are working towards, they run on AWS. They, they have, uh, a very, um, uh, secure, compliant infrastructure requirement, especially around HIPAA because they're dealing with healthcare, right? And they have needs to be able to integrate quickly and not a big budget to start with. They grew very quickly and Lummi powered their, their AWS ecosystem. So as our workloads grew on RDS, as well as SQS as three, we were able to go in and perform these HIPAA compliant integrations for them. So they could go provide reimbursement on medical spending claims for their end customers. So not only did we give them user engagement and an outstanding customer experience, we were able to help them grow as a business and be able to leverage the AWS ecosystem. That's a win, win, win across the board for all of us. >>That's one plus one equals three, for sure. Yep. One of the things too, that's interesting is, you know, when we see the plethora of AWS services, like I mentioned a minute ago, there's always so many announcements, but there's so much choice for customers, right? When you're talking ed with customers, Boomi customers that are looking for AWS services, tell me about some of those conversations. Can we help guide them along that journey? >>I mean, we help them from an architectural standpoint, as far as what services they should choose from AWS to integrate their different data sources within the AWS ecosystem and maybe to others, um, we've helped our customers going back a little bit to, to the future-proofing over the time we've at our platform, we've connected with our customers over 180,000 different data sources, including AWS and others, that as we continue to grow, our customers never need to upgrade. We're a cloud model, ourselves running an AWS. So they just get to keep taking advantage of that. Their business grows and evolves. And as AWS grows and evolves for them, and they're modernizing their infrastructure bringing in, in AWS, we continue to stay on the forefront with keeping connectivity and automation and integration options. >>And that's a massive advantage for customers in any industry, especially, I know one of the first things I thought of when the pandemic first struck and we saw this, you know, the rise of the pharma companies working on vaccine was Madrona. Madonna's a Boomi customer. If they are talk to me about some of the things that you've helped them facilitate, because there was that obviously that time where everyone's scattered, nobody could get onsite having a cloud native solution. Must've been a huge advantage. Yeah. Well getting us all back here, really >>Exactly. First and foremost, getting more people on board into their business to help go find the race for the cure. And then being able to connect that data right. That they were generating and really find a solution. So we had an integral role to play in that. That's definitely a feather in our cap. We're really proud of that. Um, again, right. It's it's about speed and agility and the way we're architected, we're a low code platform. We're not developer heavy. You can log in and go and start building right away. What, what used to take months now takes weeks. If not days, if you use the Boomi platform, those brittle code integrations no longer need to be a part of your day to day. >>And that probably was a major instrument in the survival of a lot of businesses in the very beginning when it was chaotic, right? And it was pivot, pivot, pivot, pivot, pivot, that, that, you know, one of the things we learned during the pandemic is that there is access to real-time data. Real-time integrations. Isn't a nice to have anymore. It's required. It's fundamental for employee experiences, customer experiences in every industry >>And banking. We've had several banks who were able to stand up and start taking PPP loans. Uh, they used to do this in person. They were able to take them within literally some of our banks within four days had the whole process built into it. >>Wow. And so from a differentiation perspective, how have your customer conversations changed? Obviously go Boomi. It is now is something that you do, you have t-shirts yet, by the way, they're coming. And can I get one? Yes, absolutely. Excellent. But talk to me about how those customer conversations have changed is, is what Boomi enables organizations is this snow at the C-suite the board level going? We've got to make sure that these data sources are connected because they're only gonna keep proliferating. >>Yeah, I think it's coming, right. We're not quite there yet, but as we're starting to get this groundswell at the integration developer level at the enterprise architect level, I think the C-suite especially is realizing the value of the delivery of this integrated experience now, right? These data fueled experiences are the differentiators for new business models. So transformation is something that's required. Obviously you need to modernize. We heard about that in the keynotes here at the conference, but now it's the innovation layer and that's where we're squarely focused is once you're able to connect this data and be able to modernize your systems, how do you go build new business models with innovation? That's where the C-suites leaning in with >>Us. Got it. And that's the opportunity is to really unlock the value of all this data and identify new products, new services, new target markets, and really that innovation kicks the door wide open on a competitor if you're focused on really becoming a data company, I think. Yeah, exactly. Yeah. What are some of the things that, that you're looking forward to as we, as we wrap up 2021 and let's cross our fingers, we're going into a much better 20, 22. What question for both of you and we'll start with you, what's next for Boomi? >>So we just recently laid out our hyper automation vision, right. And what hyper automation is, is adding intelligence, artificial intelligence, and machine learning to your automation to make you go faster and faster and help you with decisions that you may have been making over and over as an example, or any workflows you do as an employee. So there is this convergence of RPA and iPads that's happening in the market. And we're on the forefront of that around robotic process automation. And then bringing that, those types of things into our platform and just helping our customers automate more and more, because that's what they're looking for. That's what go Boomi. It's all about. They've integrated their stuff. We were taking the lead from our customers who are automating things. We had blue force tracking as an example, where in Amsterdam, they have security guards running around and, and, and using, um, wearable devices to track them on cameras. And that's not an application integration use case that's automation. So we're moving there, we're looking with our customers on how we can help them get faster and better and provide things like safety and that use case. So, >>And we're our customers in terms of, of embracing hyper automation. Because when we talk about, we know a lot of, uh, news around AI and, and model last day and a half, but when you think about kind of like, where are most organizations with from a maturation perspective, are they ready for hyper automation? >>I think they're ready for automation. They're learning about hyper automation. I think we're pushing the term further ahead. You know, we're, we're, we're on the forefront of that because industries are thinking, our customers are thinking about automation. They're thinking about AIML, we're introducing them to hyper automation and, and kind of explaining to them, you're doing this already. Think more along these lines, how can you drive your business forward with these? And they're embracing it really well. So >>Is that conversation elevating up to the board level yet? Is that a board level initiative or >>What it is? It's, it's a little more grassroots. I think that's, I was thinking that's where came from because the employees teams are solving problems. They're showcasing these things to their executives and saying, look at the cool stuff we're doing for the business. And the executives are now saying, well with this problem, can we now go boob? Can we Boomi it because they're there, they're starting to understand what we can do. Okay. >>That's awesome. Oh my goodness. Mandy, you've been the chief marketing officer for three over three years now. I can't believe the amount of change that you've seen, not just the last 22 months, but the last three years. What are you excited about as Boomi heads into 2022? I think, >>And new opportunities to get deeper and broader into the market. Our ownership changed as you know this past year. And, um, you know, we have a new leg on growth, if you will, right? And so whole new trajectory ahead of us, bigger brand building more pervasiveness or ease of use around our platform, right? We're available now in a pay as you go model on our website and on a $50 a month model or, uh, um, atmosphere go and then also on marketplace. So we're making the product and the platform more accessible to more people so they can begin on faster, build faster, and go solve these problems. So really democratizing integration is something that I'm very excited about. Democratizing integration, as well as more air cover, just to let people know that this technology exists. So it's really a marketer's dream >>And why they should go buy me it. Right. Exactly. You guys. It was great to have you on the program. Congratulations on the success on, on becoming a verb. That's pretty awesome. I'll look forward to my t-shirt. So I smelled flu and >>You got it. >>All right. For my guests. I'm Lisa Martin. You're watching the cube, the global leader in life tech coverage.

(upbeat music) >> Welcome back to theCUBE's continuous coverage of AWS re:Invent 2021 I'm Lisa Martin. This is our third day here on set We've got two live sets, two remote studios, over a hundred guests on the program and a lot going on with AWS and its ecosystem of partners am pleased to welcome back one of our Cube alumni, Buddy Brewer, the GVP & GM of product partnerships at New Relic. Welcome back, Buddy. Good to have you. >> Thanks it's great to be here >> Great to be in an in-person event isn't? >> No kidding it's really amazing to see everybody out here and after spending so much time on zoom calls, we had a lot of really great moments among the team and the booth playing the game of seeing if people's height matched up with >> (laughs) >> What your expectation was because so many of the people we work with >> Never mind. >> We've only known over zoom. >> Yes ,and zoom has been a savior for all of us we've been doing so much recording on zoom at the same time it's great to be here in person and seeing what a safe job AWS has done with getting I from hearing upwards of 30,000 people in here that are here in person. So talk to me about you lead the technology partnerships at New Relic. Talk to me about your role, and then we'll get into the partnership with AWS. >> Yeah, absolutely. Well, you know, the point about zoom, it's fascinating. Like you said, that just having the ability to communicate with people has been such a key enabler of being able to make progress and to continue to lead our personal and our professional lives despite the pandemic I mean, imagine what it would have been like if this had happened 10 years ago, even, but certainly 50 years ago >> Right. or something like that, right? Like everything would have ground to a halt and technology took on such an amazing, you know, critical role in allowing us to do all of these things and so at New Relic, we're all about helping people make sure that all of this software works correctly. And so observability helps people understand the detail level about everything from the front end, the end user experience to every single piece that happens along the path of delivering that experience all the way down to the infrastructure into the network. But my role at New Relic is also to help all of the other tools that software developers use every day to create those experiences that they connect into their observability platform so that they can understand all of those details and make sure that people are able to continue doing things that have become really so basic to life like ordering groceries or getting food, or, you know, communicating with a loved one over something like zoom. >> Yeah the things that to your point, if this had happened, you know, five, 10 years ago, it would have been a completely different story. We've been able to function really well and one of the things too, that, you know, I noticed yesterday and today, you probably did as well with the plethora, typical AWS the plethora of announcements, the amount of innovation that's going on, the customer flywheel that we've just seen this acceleration of technology and what it's enabling, but the observability portion is really key you talk about, you know, the developers need to the whole SDLC they need to be able to understand exactly what's going on because at the end of the day, whether it's a consumer or an enterprise of the other end of the spectrum, we need to know exactly what's going on because people's patience is far thinner these days the pandemic showed is that there is really no having access to real-time data. Isn't a luxury anymore it's really a necessity. >> Right, yeah, absolutely. >> Talk to me about some of these so a lot of announcements coming up from AWS, you guys talk to me about the partnership, what you guys are doing there. And some of the things that are exciting on that front. >> Yeah, AWS is a really key partner for us. We're big users of AWS ourselves for our observability platform and all of our infrastructure and, you know, we've had our own journey as a 13 year old business that started out pre cloud and moving our own infrastructure to the cloud. And then along that journey, we've worked closely with AWS and we've built a lot of joint solutions to help people who are moving to the cloud themselves or who are cloud native to understand all of the details about what's happening in that software so we have over 60 different integrations to all of the different tools with Amazon that you can use on the cloud from data storage, to EKS on Fargate and all of that stuff. And then we recently announced a five-year strategic agreement with Amazon to make it even easier for customers to adopt New Relic if they're building in Amazon AWS and so you know, we're in their marketplace, we have an offering for startups, for people who are just getting started that, you know, provides really simple and fast on-ramps with discounts and things like that. That's all designed to help people, software developers in particular, focus on what matters most to them, which is building great experiences for their customers. You know, you mentioned that the SDLC and this is one of the things that, you know, our mission at New Relic is to make observability a daily data-driven habit for developers across all phases of the software delivery life cycle. The problem with observability and how it's used today is that it's only used in the run phase by most people they use it when the software is on fire to put the fire out we believe that, that telemetry has tremendous strategic value in the plan, build and deploy phases of software development as well. And so partnerships like AWS allow us to unlock the accessibility of that data across all of those different phases for people who software developers are as a result in many ways that the things that we were talking about earlier with the expectations that the pandemic has placed on how software has to work, it's not an option they're busier, they're under more pressure than they've ever been before and so we want to help them relieve that pressure with tools that help them do their jobs better. >> Relieving that pressure is key there is so much pressure on developers I mean, these days from observability to security and that sort of thing, but it sounds like one of the things that you're also fundamentally doing is really shifting that observability left and helping them from a cultural perspective, it seems like almost a shift, but you're trying to make things easier for them giving them more tools and to unlock what they're not seeing right now. >> That's right and you know, the interesting thing about it is everyone realizes that observability is critical to, you know, successful software businesses so for example, we did a survey recently of 1300 software developers and IT decision makers and executives, and found that among the C-level executives that were surveyed 80% of them expected to increase their observability budget and 20% of those expected to increase it significantly. However, that same survey found that a very small percentage of those who we actually surveyed feel that they have a mature observability practice today. And when we unpack the reasons why in the survey, we found that most of them reduce down to basically this issue of they just don't have enough time to instrument all of the software, especially in a world where the shift to the cloud has driven a change in architecture where monoliths have been torn down and replaced by hundreds, or may be even thousands of microservices. >> Right. >> And we're in an era now where if observability isn't really, really easy and incredibly fast and simple to execute on then software developers can no longer instrument fast enough to keep up with the pace of the software that they're delivering and so what that leads to is visibility gaps, visibility gaps lead to poor customer experiences. And so what we're trying to do, and we've been on this massive simplification of our own platform to make it, you know, incredibly cost-effective at just 25 cents a gigabyte for ingestion and really simple licensing seat based licensing, where you get access to all of our tools to make it really simple and to take simply minutes to get observability on all those different pieces. >> If simplicity is a word that we throw around a lot, but it's really critical element and it's interesting to understand how do you actually facilitate that? You talked about, you know, kind of the 80 20 rule there. >> Yeah. >> A lot of the organization's not on that maturity curve with observability, how does New Relic and its ecosystem of partners like AWS how do you help have those conversations within organizations in any industry tell them, understand how you can actually simplify that and unlock that visibility, knowing that it's not only a matter of software development, but it's a competitive differentiator. It's also something that can damage a brand if they're not top of it. >> Yeah, we launched a re-imagined version of our partner ecosystem really our entire integration ecosystem about six weeks ago on October 13th called New Relic Instant Observability. And one of the central goals of New Relic IO, which we call it for short is to make it take just like five minutes for people to instrument something. So in the old way, what people had to do is if they wanted observability, they had to go learn about an observability vendor then they had to go install it, figure out how all that works and then they could get to solving their problem, which might've just been simply instrumenting a Kafka you know and so what we want to do is just keep people in that mode if all you wanted to do is instrument Kafka, then go find the Kafka instrumentation tile on New Relic and observability and then there's a guided install process that takes you through that and at the end you've instrumented Kafka and if you want to add something else like EKS Fargate from Amazon, or if you want to add something else like a Java service, you can simply click more of those guidance installs and add within minutes in an incremental way without having to stop and do a whole vendor evaluation to do so in fact, one of the other things that we launched recently is a free tier that's free forever. So there's no trial process or anything you don't have to put in a credit card if all you want to do is instrument this one thing right now, you can go through this process provision a free account you get access to all of our functionality for one user and ingest up to a hundred gigabytes of telemetry data for free within minutes. And so what we're trying to do is take all of that adoption friction out so that people aren't fighting with their instrumentation so much, and again, they can get back to doing what they really want to do in the first place, which has built great experiences for their end users. >> Great experiences for the end users but that translates to employee experience that translates to an end user customer experience, which translates back to brand reputation. I'm just wondering, you know, you're focused on the developers and we've been hearing a lot about the last two and a half days, a big focus on developers has observability kind of escalated up and its evolution up the stack within organizations is this a C-suite concern? Is this a board level concern? where does this fit now? and what's the vision of New Relic to deliver on that? >> With observability? >> Yes. >> Yeah, 90% of those in the survey that I was talking about felt that observability was not just a tool that they needed to use, but strategically critical to their business and, you know, this goes back to, as we know, and especially as a result of the intensity on the importance of software coming out of the pandemic, your digital business is your business these days. And so if you don't understand what's happening in that software and you can't move quickly, then you know you're really in trouble in terms of trying to succeed in a highly competitive environment and that goes back to again, one of our core beliefs is that all of this telemetry data that people have been collecting about how their software operates is so useful in contexts outside of just when there's a problem in production. Imagine if you could take that information and you could actually put it inside the IDE, which is something that we did with a recent acquisition of a company called CodeStream. We can take this telemetry data and put it inside the IDE so that as developers are writing the software, they know where those issues are. You can click straight from a stack frame, for example, inside of our, where we show all of our errors in a capability called Error's inbox and shoot right into your IDE and go see where the line of code is that caused that error, shortening that feedback loop and unlocking this really big investment that a lot of companies make in telemetry data earlier in the software life cycle, we believe is the future of observability and we want to help people get there. >> Well, the observability is really key for organizations these days because we've been hearing every company these days has to be a data company. >> Yeah. >> And it's one thing to say that it's a whole other thing to be able to implement it and observability is absolutely critical to that as being able to take that data and apply it in different contexts to really enable that business to be digital which is absolutely table-stakes these days to be successful and to deliver that customer experience ultimately. >> Yeah. >> That's what it all do. >> Yeah, absolutely. And you know, the other thing is really hard about this problem when I talk with our customers and we found this in the survey as well, is that, you know, software developers, don't just use one tool to create software they use a lot of tools in fact, 13% of those that we surveyed use 10 or more tools. >> Whoa. >> Just for the observability piece. And so, you know, obviously we're always trying to expand organically what we do inside of our platform to cover more and more use cases, but an equally important part of our strategy, if we really want to make observability a data-driven daily habit for people is to find all of those other, you know, really well-built amazing tools that those developers use and find valuable ways to integrate with them. And so that's the other part of our ecosystem that we've built out is this ability to take all of the other tools that you use and wire them into New Relic so that, for example, if you're using, let's say Lacework for security then you can, you know, if someone's installed a Bitcoin miner on your infrastructure somewhere, you can quickly navigate because of that integration from a poor customer experience through the infrastructure that's suffering may be with, you know, a lot of memory pressure, and a lot of CPU being used for this Bitcoin miner and then find out that, you know, through the integration where the miner was installed, how it got installed so that you can remediate those types of issues and connecting those pieces together, making software truly interoperable is another thing that's really critical to our mission at New Relic. >> It is critical to not only to the developers, but to the organizations and their success as businesses these days Buddy thank you for joining me, talking about what's going on at New Relic What's new, how you're really empowering those developers and all of the downstream positive effects that, that leads to we appreciate your time. >> Thank you ,thanks for having me. >> All right, you are Buddy Brewer I'm Lisa Martin you're watching theCUBE, the global leader in live tech coverage. (soft music)

>>Welcome back to the cubes, continuous coverage of AWS reinvent 2021. I'm Lisa Martin. We are winning one of the industry's most important in hybrid tech events this year with AWS and its enormous ecosystem of partners to life sets we have going on right now. There's a dueling set right across from me, two remote studios over 100 guests on the program. We'll be digging into really the next decade of cloud innovation. I'm pleased to welcome two guests that sit next to me here. We've got Aaron Arnold Santa's partner at BCG gamma and a diesel associate director of data science at BCG gamma guys. Welcome to the program. Thanks for having us. I D let's go ahead and start with you. Give us the low down what's going on at BCG gamma. >>We are focused on building responsible, sustainable, and efficient AI at scale to solve pressing business problems. >>Good. We're going to dig into that more. There was a lot of talk about AI this morning during the keynote yesterday as well. And you know, one of the things Aaron that we talked about the last day and a half is that every company, these days has to be a data company, but the volume of data is so great that we've got to have AI to be able to help all the humans process it, find all of the nuggets that are buried within these volumes of data for companies to be competitive. You talk about a sustainable efficient let's go ahead and talk about what do you mean by efficient AI? It sounds great, but help unpack what that actually means. And, and how does an organization in any industry actually achieving? >>Yeah. So when we talk about efficient AI, we're really talking about resilience, scale and adoption. So we all know that the environment in which AI tools and systems are deployed change and update very frequently, and those changes and updates can lead to errors, downtime, which erode user trust. And so when you're designing your AI, it's really critical to build it right and, and ensure it's resilient to those types of changes in the operational environment. And that really means designing it upfront to adhere to company standards around documentation, um, testing bias as well as approved model architecture. So, so that piece is really critical. The other piece about efficient AI is we're really talking about using better code structure to ensure that and enable that teams can search learn, um, and really clone AI IP to bring AI at scale across company silos. So what efficient AI does is it ensures that companies can go from proof of concept and exploration to deploying AI at scale. The final piece is really about solving the right business problems quickly in a way that ensures that users and customers will adopt and actually use the tool and capability >>That adoption there is absolutely critical. And >>You know, when we, when we're talking about AI, most of the time we're talking about three components and we call it like the ten twenty, seventy rule, 10% of the change is really about the better AI algorithms that are coming out. 20% is a better architecture, the technology, all of those components, but 70% of it is really about how are we influencing our business partners to make better decisions? How are we making sure AI is built right into the operational decision flow? And that's really, when we start talking about better AI, we move it away from kind of our pet project, buzzword bingo, into decision operational flows, you know, and, and there's, there's a journey there, there's a journey that we all are on. You see the evolution of AI right now. And I th and I liken it a lot to, um, myself when I'm, I'm a big football fan, right. And I've fantasy football is like my passion. I see. And when I look at the decision-makings, I've made 10 years ago versus now, now I actually have my own models. I'm running against it. I'm, I'm very much into the details of what is the data telling me, but, um, it's not until I bring that together with my decision making process, that really makes it so that I have bragging rights on Sundays. >>I wouldn't want to compete against Aaron. I mean, you know, I've got a lot of friends that do fantasy football, but I don't think they're taking, they're actually doing data-driven approaches as you are. One of the things I'm glad that you talked about the 10, 20, 70 formula for in dividing investments in AI. One of the things that really surprised me, and I'm looking at my notes here, because I was writing this down was that you said 10% AI and machine learning algorithms, 20% software and technology infrastructure, 70% though is also change management. That is hard, especially the speed with which every industry is operating today. What we've seen in the last 22 months, we've seen a massive acceleration to the cloud, every business pivoting, many times where our customers, in terms of understanding the challenges that they can solve with AI, given the fact that we're still in such a dynamic global environment, do what are you seeing? >>So I think it's actually quite, bi-modal some companies, including the public sector are really leaning in and exploring all the different applications and all the different solutions. Unfortunately, if they're not emphasizing that 70% on change management and the culture change and user adoption, those are substantial, but you don't get the return on the investment. Right. On the other hand, the other part of that bi-modal distribution is there are folks who are still really reluctant because they have made investments and it hasn't right. Brought about the change that they were hoping for. And so I think it's really critical to bring that holistic approach to bringing AI and advanced analytic tools to really change the way, you know, a company's attacking its problems and bringing solutions to its users and customers. >>Yeah. I like it a lot to us as us, as adults have when we teach our kids about math, right? Like less of my time with my own kids is focused on teaching them, the principles, the, and all those things, but it's more teaching them to be comfortable. Why are they learning math? What are they doing? How is that going to prepare them to be more competitive and, uh, later on in life. And so, and then the same thing's happening in this evolution in AI, right? There is this big tech and AI transformations that are happening. But the questions we need to ask ourselves within is are we taking the time to make sure our companies and our people are on the journey with us and that they understand that this is going to be better for them and give them a competitive advantage. >>That's critical. We know we've talked a lot in Alaska. We talk a lot about every show about people, process technologies and people as part of that. But I've definitely seen more of a focus. I think the last two and a half days of the people emphasis going, we have to have, we have to upskill our people. We have to train our people. We have to make sure that they're understand how this technology can partner with them and enable them rather than take things away. So it's nice to hear you talking about the big focus there being on the people that is because without that, then a deed to your point, a lot of those projects aren't successful >>And not only, I think the other piece there in terms of bringing the user along for the journey is you don't want them to feel like this is just another tool, right? Another part of their, in addition to their workflow, right? You want to take the burden away. You want it to really, um, not add, but to, to their, to their list of, of daily tasks, but subtract and make it easier. Right. And I think that that's really critical for a lot of companies as well. >>I think along with what you're talking about, we have to teach people to be responsible. So it's, it's one thing to do the job better, but it's another thing to be responsible because in today's world, we have to think about our responsibilities back to our communities, to our consumers, to our shareholders and into ultimately to the environment itself. And so responsive as we are thinking about AI, we need to think differently too, because let's face it. Data is fuel and we can accidentally make the wrong decisions for the globe by making the right decisions for stakeholders. We have to do a better job of understanding the why we're doing what we're doing, what we're doing, and not only the, the intended consequences of our decisions, but also the unintended consequences. And then we need to be responsible in the ways that we're using AI and that we're transparent in our use thereof. >>Yeah, Aaron, I think that's incredibly critical. I think responsible AI, um, has to be at the heart of, of AI transformation. And one of the interesting things that we have found is that organizations perceive their responsible AI maturity to be substantially higher than it actually is. Right. And less than 50% of organizations that have, you know, a fully implemented AI at scale, do not have a responsible AI, um, capability. And so at BCG, we've been working quite hard to integrate our gamma responsible AI program into the big AI transformations, because it's so critical. It's so absolutely important. And, and really that there's a lot of facets to that. But one of that, one of the critical ones is an ensures the goals and the outcomes of the AI systems are fair and unbiased and explainable, which is so critical. Um, I think it also ensures best that we follow best practices for data governance to protect user privacy, which I think is another critical, um, piece here, as well as minimizing any negative social or environmental impact, which again, I it's, it's just gotta be at the forefront of AI development. What about, >>And I think that there's a tech part to that too. So like one thing that we're working on called a gamma facet is really, you know, for the longest time in this AI transformation, AI was kind of a black box and it's kind of mystical, but we, we optimize our results. The transformation, when we talk about better, AI is, uh, the decision maker is in the center and knows the outcome. And so we make it a clear box. And so they're really, we're working a lot on, you know, the most common Python packages, uh, to make them more clear too, so that the business user and the data scientist understands the decisions that they're making and how it will impact the company and longer term society. >>What about the sustainability front? I mean, it's clear that I can understand why you have the 10 20, 70 approach that, that 70% is really important. There are companies that think they're much farther advanced in terms of responsible use of responsible AI responsibly than they really are. Um, but you know, we talk about sustainability all the time. It's a buzzword, but it's also something that's incredibly important to you to companies like AWS. I imagined a companies like yourself, where does, what does sustainable AI look like and how to organizations implemented along with responsible AI efficient AI? >>Yeah, I think it's the question in some ways right now, given everything that's happening around the world. And so AI for sustainability is, is really critical. I think we all have a part to play in this fight, um, to ensure our, our global environment. So I think we need to use the same AI expertise, the same AI technology that we bring to maximize revenue and minimize cost, um, to, to minimizing a company's footprint. Long-term I think that's really critical. One of the things we've seen is that 85% of companies want to reduce their emissions, but less than 10% of them know how to accurately measure right. Their footprint. And so we've been focusing on AI for sustainability across a couple of different pillars. The first is measuring the current impact from operations. The second is data mining, um, for optimal decisions to reduce that footprint. And the third is scenarios to plan better strategies to alter our impact. >>Excellent. Well, there's so much work to be done, guys. Thank you for joining me talking about what BCG is doing for responsible, efficient, ethical, and sustainable AI, a lot of opportunities. I'm sure for you guys with AWS and your list of clients, but we thank you for taking the time out to talk with us this morning. So much. I write for my guests. I'm Lisa Martin. You're watching the cube, the global leader in live tech coverage.

(upbeat music) >> Hey everyone and welcome back to the CUBE's continuous live coverage of AWS re:Invent 2021. continuous live coverage of AWS re:Invent 2021. Lisa Martin here with David Nicholson. We have two live sets going on, we've got two remote sets, over 100 guests working with AWS and it's a massive ecosystem of partners, really digging into the next decade of cloud innovation and we're pleased to welcome back one of our CUBE alumni, Edith Harbaugh, CEO, and co-founder of LaunchDarkly. We're going to be talking about a blueprint for continuous modernization, Edith, it's great to have you, thanks for coming. >> Thanks for having me. >> So I was doing some research, you guys raised 200 million in series D in August, just a few months ago, that new funding tripled your valuation to 3 billion up more than 3x from the previous funding rounds, so rocket ship. >> Edith: Yeah. >> I also noticed you guys are on the Forbes Cloud 100 2nd year on the list, you jumped dramatically from 100 in 2020 to 47 this year, talk to us about all the innovation and acceleration that's going on at LaunchDarkly. >> Yeah, well, it's, it's great to be here, you know, I'm the CEO and co-founder and we started seven years ago in 2014 and what we were doing back then was a really new field, like I actually came up with the name feature management, just to describe what we were doing and it was this idea that you could release features to different people at different times, which sounds really simple, but it really allows you to have valves to different populations that you can then turn something on, turn something off, run a beta, do personalization and then if something's going wrong out on the field quickly and easily, turn it off. >> So as an engineer, as a long standing engineer, what were the things that really frustrated you, that you thought this, this is missing, we've got to focus on this. >> Oh my gosh, so, I was an engineering manager, I actually do a podcast too called To Be Continuous just about all the bad things I saw happen, the worst thing you could do is, is build something that nobody wants, which is really frustrating, so I think a lot of continuous delivery came out of the urge to just get stuff out quicker. The flip side of that is that if you moved too fast, a release can be catastrophic. We used to call them the push and pray release because you push stuff out and then you're just crossing your fingers that nothing breaks because if something breaks it's extremely stressful. Your mind starts flooding with endorphins and hormones, your heart rate increases and you sometimes make even worse decisions, so what LaunchDarkly and feature management allow you to do is push it out to who you want and if something is going wrong, you could turn it off without a redeploy, if things are going right, you can continue to push it out. >> And when you say feature management, you're talking about, you're talking about a level of granularity that is finer than a release version. that is finer than a release version. >> Edith: Yeah. How do you do that? >> Our customers do it, so we provide a platform where our customers and we have 2,500 worldwide, everything from IBM and Atlassian, down to like three person startups, they decide how to encapsulate a feature >> David: Okay. >> So they could push it to who they want, so, so there's a lot of really neat use cases. >> So knowing that you're providing them with the valves. >> Edith: Yes. Then they can- think differently about how they're actually developing in anticipation of delivering encapsulated features, as opposed to, here's your new release. >> Edith: Exactly. >> Okay. >> Exactly, so we have some customers who've used LaunchDarkly to actually move to the cloud. So like TrueCar was running their own data centers and they wanted a way to start moving all of that data center traffic into AWS, so they could use LaunchDarkly to manage that traffic flow and do it in a controlled way instead of just one quick switch. >> I was looking at that case study of TrueCar, they migrated 500 websites to AWS without downtime and deploying 20x per day, which is up from 1x a week, that's a massive change. >> Yeah, I think really what we give our customers is confidence that if you know that you can always have control over stuff with feature management, you actually move much quicker. You can, you can move 20 times a day if you know that if something goes wrong, you can always turn it off, you have much more confidence. >> Where are your, you having customer conversations? I know you, you coined to the term feature management, I'd love to know a bit more contextually about the evolution from feature flags to feature management and where are those customer conversations happening? are they kind of down in the technical ways? are they more higher level? given the fact that we're in such a, still a, such a state of flux with COVID? >> Yeah, so we, we didn't invent feature flagging like the smart companies like Amazon, Facebook, Netflix have been doing feature flagging for decades now, it was always a secret sauce of this is how they could manage their own functionality. What LaunchDarkly did was kind of changed it to feature management about doing it where any other customer also had the same set of tools and platforms and also on top of that things like a workflow, scheduling, integrations. So that for example, a developer could develop something and then give the keys to the product manager, say product manager, you get to, you get to run the beta now. >> So putting, putting more control back in the hands of the folks that are, that really are touching and feeling and smelling the product. >> Yeah or customer support, you know, >> Yeah or customer support, you know, if something is going wrong in the field, instead of having to wait for an engineer to fix a bug customer support could just turn it off. >> So I'm curious about, you know, when we talk about it's a, this, this sort of dovetails with something that was discussed in the keynote today, out of the gate, Adam comes out and he's talking about microprocessor technology. Now in the era of cloud, generally people would say, that stuff doesn't matter, right? It's all about the feeling of being in the cloud and the flame, you know, the, the, the field of wheat blowing in the wind and it's a feeling that you get, it's really interesting what you're doing under the covers, but who is the, who is the audience? Who, who buys this? Because I can imagine some in the engineering, on the engineering side of things, feeling like maybe they're giving up some control, but really you're giving them more tools, but is it business people who are demanding this? how, how do you go to market? >> Yeah, so it's really interesting because our core audience is developers and VP of engineering, like they love the platform. Like our Net Promoter Score is extremely high, engineers say like, this gave me my weekends back because if a bug happens I don't have to come in. >> David: Okay so they get it. >> They get it. This isn't being pushed down- from executives that don't understand the technology. >> No, I mean, a typical thing is a developer's, like, I need this to do my job and then the business people say, well, if the developers are happy, we're happy, you know, it's, it's a developers world now, you know, they're hard to hire, you have to have them and if you have anything that will make their job easier and them happier, why wouldn't you buy it? >> That's a big facilitator, so you mentioned a high, high NPS, high Net Promoter Score, we, we talk with Amazon folks about their their focus on the customer and their customer obsession if you will, that everything starts backwards, we start from the customer, 2,500 customers in such a short time period, we talked about the funding, I imagine culturally there's similarities there, if one of the things that you're able to confidently give your customers is that confidence in LaunchDarkly. >> Yeah, you know, one of the happiest parts of my job is visiting customers, you know, I, my co-founder and I personally visited, I think the first 10 or 20 customers and if they had a bug, if they wanted something, and if they had a bug, if they wanted something, we built it. And I love going on customer sites, cause it's. And I love going on customer sites, cause it's. >> When they're telling you that you gave them their weekend back. >> Edith: Yeah. >> Huge. >> That's, yeah, that.- that's not an insignificant thing when you think about what people do with their weekends, you know, so? >> Yeah, you know, it, it feels really good to have customers say, like this literally has changed the way they built software for the better. >> I can't imagine this, you know, with everything that's happened in the last 22 months with the acceleration to cloud, but all these massive pivots by businesses, in every industry just to survive in the beginning, were an advantage, something like LaunchDarkly is for those organizations, so you have to move really, really quickly and keep changing direction to kind of figure out how do we stay afloat and now how do we thrive in that, that this has probably been a real lifesaver for a lot of organizations. >> Yeah, I mean, we've seen like a ten year roadmap at our customers compressed into a month, like we had a, a retail chain in the Midwest that was thinking about doing in-store pickup and then when COVID hit, they're like, okay, this changed from a, maybe to a, we need to have this to stay afloat and now, now they can help people pick up, same with, same with restaurants having a mobile app to do delivery or pickup, it used to be when we'll get to that next year, now it's something that you have to have. >> Oh yeah. >> Because if, if you're going to go get coffee and one place has a mile long line and their place has an app, which one are you going to pick? >> So, what do people do that don't have this capability? This, I mean, this might sound like a completely naive question, I know a lot about a lot of things, so I'm okay looking dumb sometimes, it's how I learn, so I'm okay looking dumb sometimes, it's how I learn, but seriously, if you don't have these valves, then aren't you doomed then aren't you doomed to releases that are going to be panic inducing. >> It's really, it's really painful, like, I mean, that's, that's the way I used to, to release, you know, I remember it, like you're released and you would have tried to have caught all the bugs, but it would go out and if something happened, you had to fix it on the fly and even if you have a really good deployment process, that's 20 minutes, maybe two hours. >> David: Sure, and, and. >> Which, which if you're a mobile app, it could be a business killer. >> Yeah, well we're here at AWS reinvent, I mean, how does, how does this dovetail with this, the AWS mission to migrate and modernize into the cloud native world? we're talking about cloud native, you know, development and operations that you're involved with, so there's obviously a synergy there, but why specifically AWS? >> Oh, I mean, I think one of the biggest tailwinds we've had as a business is if you're releasing twice a year, we've had as a business is if you're releasing twice a year, you don't really need a tool like this, or a platform like this, your business process is completely different, but you're going to die as a company cause you can't survive on two releases a year. If you're moving to the cloud, we help you get there and once you're in the cloud, if you want to move at the speed of business, but safely, we give you that platform. Like, so, I think continuous delivery got this bad wrap because people thought that meant that you push out stuff every second and break everything. >> David: Right. >> What we do is we allow you to innovate as fast as you want, but release in a controlled way. >> I got to ask you a question, you, you talked about the customers and your love of being with customers, one of the things I can't help thinking is that what you're helping facilitate is brand reputation. If, you know, if we have an expectation and we want to go on a, on an app and order coffee, and it's down, we're going to go to the next competitor, so from a brand reputation perspective, I'm just wondering if, if any of your customer conversations kind of go in addition to the VP of engineering kind of go in addition to the VP of engineering and it focused on the folks that are leading these companies going, our reputation is on the line, people are, let's face it during COVID far less patience than we've, we've seen a lot of really impatient people, but is, is that something that you also facilitate, is the brand reputation? >> Oh, not just a brand reputation that an outage can be costly of millions of dollars, like. that an outage can be costly of millions of dollars, like. >> Lisa: $5,600 a minute, I think is what Gartner estimates. >> Yeah, but depending on what business you're in, like if you're in a bank, you absolutely need to be reliable. If you're a streaming service like streaming, one of the biggest horse races in Australia, you need to have uptime. >> Everybody needs uptime, let's, let's just be clear if I can't get door dash or whatever, it's a disaster from my perspective as a consumer and yes, we have, we have far less patience than we've ever had. >> Yeah, I mean, we have a really interesting, we have both B2C, like streaming ash, streaming apps, delivery apps, as well as B2B streaming apps, delivery apps, as well as B2B and they both have problems that we solve but honestly, the, the, the business problems with a B2B are much more challenging sometimes. >> Well Edith, thank you so much for joining David and me on the program, talking about LaunchDarkly, what you're enabling organizations to achieve in every industry, it sounds like you're riding a rocket ship. >> It's been really fun, you know, I, I love seeing a customer that's been using us for three, five years. >> David: Wow. >> And how much their life has gotten better. >> And as you said, that's, that's no small statement. Thank you so much for joining us on the program, we appreciate your insights and look forward to hearing more news from LaunchDarkly coming out. >> Thanks. >> All right, for David Nicholson, I'm Lisa Martin, you're watching theCUBE's coverage of AWS:reinvent 2021, theCUBE, the global leader in live tech coverage. (upbeat music)